14 jobs found

High Performance Workstation Business Development Manager- AMD Description - Sales and Technical Consultant, High-Performance Workstation Segment We are seeking a customer-facing AI and Acquisition subject matter expert role on the HPI Advanced Compute Solutions (ACS) sales team and will focus on growing HP's Z high-performance workstation Total Addressable Market (TAM) within the AI PC market. This individual will be responsible for working with customers and partners in support of attracting new customers and growth in HP's high performance compute solutions . The role analyzes market competition, gathers customer feedback, and shares insights with internal teams for improvement. The ideal candidate will possess a breadth of abilities and skills, including client hardware knowledge, AI and machine learning applications and solutions, strong marketing and presentation skills, solid understanding of customers' business and decision makers, and strong team leadership to drive growth with an emphasis on Advanced Micro Devices (AMD) platforms with customers and partners. Most importantly, the role offers the opportunity to be a business leader in support of the sales teams nationally - contributing to the strategy, setting direction, and achieving success in AMD and HP. The role requires someone to be self-driven, capable of operating autonomously through ambiguity, and constantly striving for excellence. THE PERSON: We seek an individual with exceptional technical & business knowledge and familiarity with AI trends in the PC market. This individual should be comfortable working: Dynamic environment and have experience with PC client and AI hardware, software and systems. Work independently within a core team is important, and you will rely upon your excellent communication and relationship building skills during customer engagements. Collaborate closely with the HP extended sales team including workstation, and general sales, regional sales leadership, category teams well as alliance partners to drive successful outcomes with our customers and partners. Important Attributes: Knowledge: Understanding of PC systems microprocessors, specifically advanced micro devices is highly valued. Proactive & Collaborative: Strong positive can-do attitude willing to do what is necessary and lead others in the wider sales team by example. Available to help colleagues. Results-Driven: Skilled in independently prioritizing opportunities to deliver results on time. Problem-Solving: Inquiring mind, excellent problem-solving skills Effective Communicator: Strong communication skills to articulate findings to both product management, engineering, sales and leadership. Team Player: Collaborative and strong team player Travel Flexibility: Open to travel domestically, approximately >50% KEY RESPONSIBILITIES: Customer Engagement: Engage with the largest and most strategic customers and partners in the assigned region to develop a keen understanding of their goals, strategies, and technical needs. Help to define and deliver the HPI and AMD solutions that meet those needs. Sales Support: Assist the customer and our partners through the qualification, sales and delivery phase. Partners with field sales teams to create and present customized solutions and proposals that address the client's needs. Trusted Advisor: Be a trusted advisor for largest acquisition customers and be an AMD ambassador for the broader sales community. Assist customers in building creative solutions based on AMD technologies where possible. Knowledge Sharing: Build a body of documentation for internal and external dissemination. HPI and AMD-internal guides, whitepapers, performance guides and training collateral. Customer Guidance: Liaise and advise customers and partners through Proof of Concepts, presentations, and training. Product Advocacy: Provide customer requirements to both AMD and HP product teams to foster platform improvements. Industry Leadership: Be a segment leader with a vision for integrating HPI and AMD technologies into customers workloads and environments. TCO Models & Pricing: Assist in creating TCO models to assist pricing with bid desk leveraging the AMD relationship directly. Clearly articulate the customer value and cost advantages of AMD-based platforms to support informed decision-making and drive solution adoption. Industry Networking: Attend industry events and seminars to stay updated on new techniques and technologies and continuously adapt in a rapidly changing business environment to enhance sales efforts. PREFERRED EXPERIENCE: Sales or Pre-Sales experience in end customer and partner engagements. Experience and understanding of personal computer microprocessors with an emphasis on AMD is highly valued. Knowledge of Artificial Intelligence (AI) and Machine Learning (ML) concepts and techniques, as well as practical experience applying these concepts to solve real-world problems through research or work experience. Familiarity with large public procurements and co-design engagements Customer-facing experience. Able to write technical documents and communicate at an appropriate level depending on the audience. ACADEMIC CREDENTIALS: Bachelors' Degree in a technical or sales field (Computer Science, Electrical Engineering, Business Management) preferred; MBA appreciated. LOCATION: Primary: Houston, TX. Secondary: Austin, TX The on-target earnings (OTE) range for this role is $165,450 to $280,000 USD annually with a 60%/40% (salary/incentive) mix. There are additional opportunities for pay in the form of bonuses and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 13 paid holidays Additional flexible paid vacation and sick leave (US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Sales Schedule - Full time Shift - No shift premium (United States of America) Travel - 50% Relocation - No Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy () or read about your rights as an applicant under the law here: "Know Your Rights: Workplace Discrimination is Illegal () "

High Performance Workstation Business Development Manager- AMD Description - Sales and Technical Consultant, High-Performance Workstation Segment We are seeking a customer-facing AI and Acquisition subject matter expert role on the HPI Advanced Compute Solutions (ACS) sales team and will focus on growing HP's Z high-performance workstation Total Addressable Market (TAM) within the AI PC market. This individual will be responsible for working with customers and partners in support of attracting new customers and growth in HP's high performance compute solutions . The role analyzes market competition, gathers customer feedback, and shares insights with internal teams for improvement. The ideal candidate will possess a breadth of abilities and skills, including client hardware knowledge, AI and machine learning applications and solutions, strong marketing and presentation skills, solid understanding of customers' business and decision makers, and strong team leadership to drive growth with an emphasis on Advanced Micro Devices (AMD) platforms with customers and partners. Most importantly, the role offers the opportunity to be a business leader in support of the sales teams nationally - contributing to the strategy, setting direction, and achieving success in AMD and HP. The role requires someone to be self-driven, capable of operating autonomously through ambiguity, and constantly striving for excellence. THE PERSON: We seek an individual with exceptional technical & business knowledge and familiarity with AI trends in the PC market. This individual should be comfortable working: Dynamic environment and have experience with PC client and AI hardware, software and systems. Work independently within a core team is important, and you will rely upon your excellent communication and relationship building skills during customer engagements. Collaborate closely with the HP extended sales team including workstation, and general sales, regional sales leadership, category teams well as alliance partners to drive successful outcomes with our customers and partners. Important Attributes: Knowledge: Understanding of PC systems microprocessors, specifically advanced micro devices is highly valued. Proactive & Collaborative: Strong positive can-do attitude willing to do what is necessary and lead others in the wider sales team by example. Available to help colleagues. Results-Driven: Skilled in independently prioritizing opportunities to deliver results on time. Problem-Solving: Inquiring mind, excellent problem-solving skills Effective Communicator: Strong communication skills to articulate findings to both product management, engineering, sales and leadership. Team Player: Collaborative and strong team player Travel Flexibility: Open to travel domestically, approximately >50% KEY RESPONSIBILITIES: Customer Engagement: Engage with the largest and most strategic customers and partners in the assigned region to develop a keen understanding of their goals, strategies, and technical needs. Help to define and deliver the HPI and AMD solutions that meet those needs. Sales Support: Assist the customer and our partners through the qualification, sales and delivery phase. Partners with field sales teams to create and present customized solutions and proposals that address the client's needs. Trusted Advisor: Be a trusted advisor for largest acquisition customers and be an AMD ambassador for the broader sales community. Assist customers in building creative solutions based on AMD technologies where possible. Knowledge Sharing: Build a body of documentation for internal and external dissemination. HPI and AMD-internal guides, whitepapers, performance guides and training collateral. Customer Guidance: Liaise and advise customers and partners through Proof of Concepts, presentations, and training. Product Advocacy: Provide customer requirements to both AMD and HP product teams to foster platform improvements. Industry Leadership: Be a segment leader with a vision for integrating HPI and AMD technologies into customers workloads and environments. TCO Models & Pricing: Assist in creating TCO models to assist pricing with bid desk leveraging the AMD relationship directly. Clearly articulate the customer value and cost advantages of AMD-based platforms to support informed decision-making and drive solution adoption. Industry Networking: Attend industry events and seminars to stay updated on new techniques and technologies and continuously adapt in a rapidly changing business environment to enhance sales efforts. PREFERRED EXPERIENCE: Sales or Pre-Sales experience in end customer and partner engagements. Experience and understanding of personal computer microprocessors with an emphasis on AMD is highly valued. Knowledge of Artificial Intelligence (AI) and Machine Learning (ML) concepts and techniques, as well as practical experience applying these concepts to solve real-world problems through research or work experience. Familiarity with large public procurements and co-design engagements Customer-facing experience. Able to write technical documents and communicate at an appropriate level depending on the audience. ACADEMIC CREDENTIALS: Bachelors' Degree in a technical or sales field (Computer Science, Electrical Engineering, Business Management) preferred; MBA appreciated. LOCATION: Primary: Houston, TX. Secondary: Austin, TX The on-target earnings (OTE) range for this role is $165,450 to $280,000 USD annually with a 60%/40% (salary/incentive) mix. There are additional opportunities for pay in the form of bonuses and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 13 paid holidays Additional flexible paid vacation and sick leave (US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Sales Schedule - Full time Shift - No shift premium (United States of America) Travel - 50% Relocation - No Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy () or read about your rights as an applicant under the law here: "Know Your Rights: Workplace Discrimination is Illegal () "

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity As a dedicated Director, Data Scientist, you will lead a team of Data Scientists responsible for identifying, scoping, and translating business problems into applied statistical, machine learning, simulation, and optimization solutions that generate actionable business insights and drive business value through automation, revenue generation, and the reduction of expenses and risk. You will work closely with business leaders to ideate, evaluate, and scope projects that address critical business needs. You will manage the team's project portfolio and communicate progress, outcomes, and key updates to senior leadership and other business stakeholders. Additionally, you will be responsible for the team's model inventory, ensuring compliance with USAA's model risk management policies and regulatory requirements. You will influence the future of data science at USAA by researching emerging technologies, identifying opportunities for innovation, and driving the adoption of advanced analytical capabilities across the organization. We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, or Tampa, FL. Relocation assistance is not available for this position. What you'll do: Acts as advanced analytics thought leader and advisor to the business to shape strategies that drive competitiveness and differentiation. Influences business, data, and technology leaders to invest, sustain and expand advanced analytical capabilities by actively participating in strategy, planning, and budgeting exercises. Leads and develops team to build and deploy various advanced analytical solutions in an agile and collaborative environment across business, data, and technology organizations. Enables team's success by simplifying processes across the model development lifecycle and driving automation. Identifies, scopes, and manages complex analytical projects in collaboration with business stakeholders, often translating results to non-technical business executives. Champions and manages efforts to deliver business insights via scalable, automated solutions using machine learning, simulation, and optimization. Responsible for ensuring all modeling and machine learning solutions adhere to industry standards, model risk policy, and regulatory expectations. Partners with enterprise analytical and IT teams to build USAA core capabilities and processes. Identifies additional resource needs ranging from IT investments, 3rd party support or additional analysts. Builds and oversees a team of Data Scientists through ongoing execution of recruiting, development, retention, coaching and support, performance management, and managerial activities. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Bachelor's degree in Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science, or a business or quantitative field; OR 4 years of relevant education and/or experience. 8 years in predictive modeling, model governance, machine learning and large data analysis., OR Advanced Degree (e.g., Master's, PhD) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative STEM field (Science, Technology, Engineering and Math) field and 6 years in predictive modeling, model governance, machine learning and large data analysis. 3 years of direct management experience. Strong communication skills; demonstrated ability to interpret and translate complex technical information to diverse audiences. Experience with various languages, applications, and technologies (such as SQL, Python, R, Spark, Hadoop etc.) commonly associated with delivery of Data Science solutions. Experience in developing and reviewing modeling solutions based on broad range of techniques - e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques. Demonstrated ability to apply best practices in modeling and machine learning techniques to solve business problems. Demonstrated ability to write and review complex technical documentation, communicate modeling insights and technical details to business leaders, technical and non-technical audiences. A strong track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent). Deep technical skills, consulting experience, and business savvy to interface with all levels and disciplines within the organization. What sets you apart: US military experience gained through military service or gained as a military spouse / domestic partner. Financial Services industry experience. Compensation range: The salary range for this position is: $189,370 - $361,950. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job. Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals. For more details on our outstanding benefits, visit our benefits page on Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting. USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity As a dedicated Director, Data Scientist, you will lead a team of Data Scientists responsible for identifying, scoping, and translating business problems into applied statistical, machine learning, simulation, and optimization solutions that generate actionable business insights and drive business value through automation, revenue generation, and the reduction of expenses and risk. You will work closely with business leaders to ideate, evaluate, and scope projects that address critical business needs. You will manage the team's project portfolio and communicate progress, outcomes, and key updates to senior leadership and other business stakeholders. Additionally, you will be responsible for the team's model inventory, ensuring compliance with USAA's model risk management policies and regulatory requirements. You will influence the future of data science at USAA by researching emerging technologies, identifying opportunities for innovation, and driving the adoption of advanced analytical capabilities across the organization. We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, or Tampa, FL. Relocation assistance is not available for this position. What you'll do: Acts as advanced analytics thought leader and advisor to the business to shape strategies that drive competitiveness and differentiation. Influences business, data, and technology leaders to invest, sustain and expand advanced analytical capabilities by actively participating in strategy, planning, and budgeting exercises. Leads and develops team to build and deploy various advanced analytical solutions in an agile and collaborative environment across business, data, and technology organizations. Enables team's success by simplifying processes across the model development lifecycle and driving automation. Identifies, scopes, and manages complex analytical projects in collaboration with business stakeholders, often translating results to non-technical business executives. Champions and manages efforts to deliver business insights via scalable, automated solutions using machine learning, simulation, and optimization. Responsible for ensuring all modeling and machine learning solutions adhere to industry standards, model risk policy, and regulatory expectations. Partners with enterprise analytical and IT teams to build USAA core capabilities and processes. Identifies additional resource needs ranging from IT investments, 3rd party support or additional analysts. Builds and oversees a team of Data Scientists through ongoing execution of recruiting, development, retention, coaching and support, performance management, and managerial activities. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Bachelor's degree in Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science, or a business or quantitative field; OR 4 years of relevant education and/or experience. 8 years in predictive modeling, model governance, machine learning and large data analysis., OR Advanced Degree (e.g., Master's, PhD) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative STEM field (Science, Technology, Engineering and Math) field and 6 years in predictive modeling, model governance, machine learning and large data analysis. 3 years of direct management experience. Strong communication skills; demonstrated ability to interpret and translate complex technical information to diverse audiences. Experience with various languages, applications, and technologies (such as SQL, Python, R, Spark, Hadoop etc.) commonly associated with delivery of Data Science solutions. Experience in developing and reviewing modeling solutions based on broad range of techniques - e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques. Demonstrated ability to apply best practices in modeling and machine learning techniques to solve business problems. Demonstrated ability to write and review complex technical documentation, communicate modeling insights and technical details to business leaders, technical and non-technical audiences. A strong track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent). Deep technical skills, consulting experience, and business savvy to interface with all levels and disciplines within the organization. What sets you apart: US military experience gained through military service or gained as a military spouse / domestic partner. Financial Services industry experience. Compensation range: The salary range for this position is: $189,370 - $361,950. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job. Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals. For more details on our outstanding benefits, visit our benefits page on Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting. USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity As a dedicated Director, Data Scientist, you will lead a team of Data Scientists responsible for identifying, scoping, and translating business problems into applied statistical, machine learning, simulation, and optimization solutions that generate actionable business insights and drive business value through automation, revenue generation, and the reduction of expenses and risk. You will work closely with business leaders to ideate, evaluate, and scope projects that address critical business needs. You will manage the team's project portfolio and communicate progress, outcomes, and key updates to senior leadership and other business stakeholders. Additionally, you will be responsible for the team's model inventory, ensuring compliance with USAA's model risk management policies and regulatory requirements. You will influence the future of data science at USAA by researching emerging technologies, identifying opportunities for innovation, and driving the adoption of advanced analytical capabilities across the organization. We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, or Tampa, FL. Relocation assistance is not available for this position. What you'll do: Acts as advanced analytics thought leader and advisor to the business to shape strategies that drive competitiveness and differentiation. Influences business, data, and technology leaders to invest, sustain and expand advanced analytical capabilities by actively participating in strategy, planning, and budgeting exercises. Leads and develops team to build and deploy various advanced analytical solutions in an agile and collaborative environment across business, data, and technology organizations. Enables team's success by simplifying processes across the model development lifecycle and driving automation. Identifies, scopes, and manages complex analytical projects in collaboration with business stakeholders, often translating results to non-technical business executives. Champions and manages efforts to deliver business insights via scalable, automated solutions using machine learning, simulation, and optimization. Responsible for ensuring all modeling and machine learning solutions adhere to industry standards, model risk policy, and regulatory expectations. Partners with enterprise analytical and IT teams to build USAA core capabilities and processes. Identifies additional resource needs ranging from IT investments, 3rd party support or additional analysts. Builds and oversees a team of Data Scientists through ongoing execution of recruiting, development, retention, coaching and support, performance management, and managerial activities. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Bachelor's degree in Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science, or a business or quantitative field; OR 4 years of relevant education and/or experience. 8 years in predictive modeling, model governance, machine learning and large data analysis., OR Advanced Degree (e.g., Master's, PhD) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative STEM field (Science, Technology, Engineering and Math) field and 6 years in predictive modeling, model governance, machine learning and large data analysis. 3 years of direct management experience. Strong communication skills; demonstrated ability to interpret and translate complex technical information to diverse audiences. Experience with various languages, applications, and technologies (such as SQL, Python, R, Spark, Hadoop etc.) commonly associated with delivery of Data Science solutions. Experience in developing and reviewing modeling solutions based on broad range of techniques - e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques. Demonstrated ability to apply best practices in modeling and machine learning techniques to solve business problems. Demonstrated ability to write and review complex technical documentation, communicate modeling insights and technical details to business leaders, technical and non-technical audiences. A strong track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent). Deep technical skills, consulting experience, and business savvy to interface with all levels and disciplines within the organization. What sets you apart: US military experience gained through military service or gained as a military spouse / domestic partner. Financial Services industry experience. Compensation range: The salary range for this position is: $189,370 - $361,950. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job. Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals. For more details on our outstanding benefits, visit our benefits page on Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting. USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity As a dedicated Director, Data Scientist, you will lead a team of Data Scientists responsible for identifying, scoping, and translating business problems into applied statistical, machine learning, simulation, and optimization solutions that generate actionable business insights and drive business value through automation, revenue generation, and the reduction of expenses and risk. You will work closely with business leaders to ideate, evaluate, and scope projects that address critical business needs. You will manage the team's project portfolio and communicate progress, outcomes, and key updates to senior leadership and other business stakeholders. Additionally, you will be responsible for the team's model inventory, ensuring compliance with USAA's model risk management policies and regulatory requirements. You will influence the future of data science at USAA by researching emerging technologies, identifying opportunities for innovation, and driving the adoption of advanced analytical capabilities across the organization. We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, or Tampa, FL. Relocation assistance is not available for this position. What you'll do: Acts as advanced analytics thought leader and advisor to the business to shape strategies that drive competitiveness and differentiation. Influences business, data, and technology leaders to invest, sustain and expand advanced analytical capabilities by actively participating in strategy, planning, and budgeting exercises. Leads and develops team to build and deploy various advanced analytical solutions in an agile and collaborative environment across business, data, and technology organizations. Enables team's success by simplifying processes across the model development lifecycle and driving automation. Identifies, scopes, and manages complex analytical projects in collaboration with business stakeholders, often translating results to non-technical business executives. Champions and manages efforts to deliver business insights via scalable, automated solutions using machine learning, simulation, and optimization. Responsible for ensuring all modeling and machine learning solutions adhere to industry standards, model risk policy, and regulatory expectations. Partners with enterprise analytical and IT teams to build USAA core capabilities and processes. Identifies additional resource needs ranging from IT investments, 3rd party support or additional analysts. Builds and oversees a team of Data Scientists through ongoing execution of recruiting, development, retention, coaching and support, performance management, and managerial activities. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Bachelor's degree in Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science, or a business or quantitative field; OR 4 years of relevant education and/or experience. 8 years in predictive modeling, model governance, machine learning and large data analysis., OR Advanced Degree (e.g., Master's, PhD) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative STEM field (Science, Technology, Engineering and Math) field and 6 years in predictive modeling, model governance, machine learning and large data analysis. 3 years of direct management experience. Strong communication skills; demonstrated ability to interpret and translate complex technical information to diverse audiences. Experience with various languages, applications, and technologies (such as SQL, Python, R, Spark, Hadoop etc.) commonly associated with delivery of Data Science solutions. Experience in developing and reviewing modeling solutions based on broad range of techniques - e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques. Demonstrated ability to apply best practices in modeling and machine learning techniques to solve business problems. Demonstrated ability to write and review complex technical documentation, communicate modeling insights and technical details to business leaders, technical and non-technical audiences. A strong track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent). Deep technical skills, consulting experience, and business savvy to interface with all levels and disciplines within the organization. What sets you apart: US military experience gained through military service or gained as a military spouse / domestic partner. Financial Services industry experience. Compensation range: The salary range for this position is: $189,370 - $361,950. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job. Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals. For more details on our outstanding benefits, visit our benefits page on Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting. USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale. You'll lead the detailed technical design, development, and implementation of core agentic architectures and multi-agent workflows using emerging technologies. You'll focus on system-level architectural design, develop and review complex models and application code, and ensure the high availability, performance, and security of our generative AI applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in generative and agentic machine learning engineering. What you'll do in the role: Architect Agentic Platforms: Design, develop, and scale core agentic engines and multi-agent workflow solutions, enabling seamless composition of conversational and business automation workflows. Drive AI Evaluation & Trust: Build and integrate scalable evaluation (Evals) and observability frameworks into solutions to ensure model predictability, performance monitoring, and mitigation of model risk. Deliver High-Impact Use Cases: Partner with cross-functional product and business teams to deploy production AI solutions, including next-generation consumer AI experiences, intelligent recommendation engines, and advanced conversational assistants. Enforce Enterprise Guardrails: Ensure all AI/ML applications strictly adhere to robust data privacy standards, regulatory postures, and framework auditability/explainability. Translate Practical Research: Stay abreast of practical advancements in LLM optimization, retrieval-augmented generation (RAG), and multi-agent design patterns, judiciously applying these novel techniques to production systems. Technical Leadership & Code Excellence: Provide technical direction, architectural oversight, and rigorous code reviews for engineering teams, fostering a culture of modern engineering excellence. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with GenAI frameworks (e.g., LangChain, LangGraph, LlamaIndex) and Vector Databases 3 years of experience building, scaling, and optimizing Large Language Model (LLM) or GenAI orchestration systems in production 2+ years of experience building automated evaluations (Evals) and observability pipelines for LLMs 3+ years of on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow Experience deploying AI solutions within a strictly regulated environment, incorporating data privacy and model risk governance Demonstrated ability to lead technical architecture design and provide deep technical guidance to engineering teams Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform ML industry impact through conference presentations, papers, blog posts, open-source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Plano, TX: $179,400 - $204,700 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Lead Machine Learning Engineer (Manager IC) At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class talent along with our deep experience in machine learning position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine exceptional products for our customers. In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers. Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI. Fine-tune, develop and evaluate machine learning and foundation models, Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One. Leverage a broad stack of Open Source and SaaS AI technologies. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues. Retrain, maintain, and monitor models in production. Construct optimized data pipelines to feed ML models. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. You are a passionate communicator, comfortable with explaining complex technical concepts to non-technical partners across the business, sometimes in front of large audiences. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production Strategic & Business-Oriented: think beyond the technology, deeply understanding business needs and how AI can solve them. You don't just build; you strategize and prioritize work that delivers the greatest business value. Highly Collaborative & Transparent: You are a natural partner, working seamlessly across engineering, product, and data science teams. You communicate your progress, blockers, and decisions clearly and proactively, ensuring everyone is aligned. You love sharing knowledge and insights and are committed to the success of the entire team. Technically Mature & Humble: You possess a strong foundation in engineering and mathematics. You are a resilient problem-solver who can bring clarity to complex, undefined problems and articulate your findings concisely. You demonstrate professional maturity by committing to and executing on team decisions. Flexible & Fungible: You are eager to roll up your sleeves and contribute wherever the team needs you most. You are comfortable working across different aspects of the tech stack and adapting to evolving priorities. A Lifelong Learner: You love staying current with the latest AI research and can apply novel techniques to production systems judiciously, always with a focus on business impact. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 7+ years of experience designing, developing, delivering, and supporting AI services at scale 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation (RAG) 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace . click apply for full job details

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine exceptional products for our customers. In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers. Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI. Fine-tune, develop and evaluate machine learning and foundation models, Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One. Leverage a broad stack of Open Source and SaaS AI technologies. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues. Retrain, maintain, and monitor models in production. Construct optimized data pipelines to feed ML models. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. You are a passionate communicator, comfortable with explaining complex technical concepts to non-technical partners across the business, sometimes in front of large audiences. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production Strategic & Business-Oriented: You think beyond the technology, deeply understanding business needs and how AI can solve them. You don't just build; you strategize and prioritize work that delivers the greatest business value. Highly Collaborative & Transparent: You are a natural partner, working seamlessly across engineering, product, and data science teams. You communicate your progress, blockers, and decisions clearly and proactively, ensuring everyone is aligned. You love sharing knowledge and insights and are committed to the success of the entire team. Technically Mature & Humble: You possess a strong foundation in engineering and mathematics. You are a resilient problem-solver who can bring clarity to complex, undefined problems and articulate your findings concisely. You demonstrate professional maturity by committing to and executing on team decisions. Flexible & Fungible: You are eager to roll up your sleeves and contribute wherever the team needs you most. You are comfortable working across different aspects of the tech stack and adapting to evolving priorities. A Lifelong Learner: You love staying current with the latest AI research and can apply novel techniques to production systems judiciously, always with a focus on business impact. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 7+ years of experience designing, developing, delivering, and supporting AI services at scale 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation (RAG) 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace . click apply for full job details

Lead Machine Learning Engineer (Manager IC) At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class talent along with our deep experience in machine learning position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine exceptional products for our customers. In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers. Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI. Fine-tune, develop and evaluate machine learning and foundation models, Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One. Leverage a broad stack of Open Source and SaaS AI technologies. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues. Retrain, maintain, and monitor models in production. Construct optimized data pipelines to feed ML models. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. You are a passionate communicator, comfortable with explaining complex technical concepts to non-technical partners across the business, sometimes in front of large audiences. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production Strategic & Business-Oriented: think beyond the technology, deeply understanding business needs and how AI can solve them. You don't just build; you strategize and prioritize work that delivers the greatest business value. Highly Collaborative & Transparent: You are a natural partner, working seamlessly across engineering, product, and data science teams. You communicate your progress, blockers, and decisions clearly and proactively, ensuring everyone is aligned. You love sharing knowledge and insights and are committed to the success of the entire team. Technically Mature & Humble: You possess a strong foundation in engineering and mathematics. You are a resilient problem-solver who can bring clarity to complex, undefined problems and articulate your findings concisely. You demonstrate professional maturity by committing to and executing on team decisions. Flexible & Fungible: You are eager to roll up your sleeves and contribute wherever the team needs you most. You are comfortable working across different aspects of the tech stack and adapting to evolving priorities. A Lifelong Learner: You love staying current with the latest AI research and can apply novel techniques to production systems judiciously, always with a focus on business impact. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 7+ years of experience designing, developing, delivering, and supporting AI services at scale 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation (RAG) 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace . click apply for full job details

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity This role is remote eligible in the continental U.S. with occasional business travel. However, individuals residing within a 60-mile radius of a USAA office will be expected to work on-site four days per week. Relocation assistance is not available for this position. Job Description The Lead Graph Data Scientist - Identity Analytics is responsible for development and implementing quantitative solutions that improve USAA's ability to detect and prevent identity theft, account takeover, and first-party/synthetic fraud. These solutions range from machine learning model development to enterprise deployment of graph analytics capabilities that protect USAA and our Members from these threats. Strong candidates will be able to deliver the following work products and processes: Develop and continuously update internal identity theft and authentication models to mitigate fraud losses and reduce negative member experience from fraud applications, synthetic fraud, and account takeover attempts Closely partner with the Strategy team, Director of Fraud Identity Analytics, Director of Fraud Model Management, and model users on model builds and priorities. Partner with Technology and other key collaborators to deploy a Member Protection graph technology strategy, including vendor selection, business requirements, data needs, and clear use cases spanning financial crimes Deploy graph databases and graph techniques to identify criminal networks engaging in fraud, scams, disputes/claims, and AML, improving fraud detection and loss mitigation Generate and prioritize fraud-dense rings to mitigate losses and improve Member experience Identify and work with technology to integrate new data sources for models and graphs to augment predictive power and improve business performance Exports insights to decision systems to enable better fraud targeting and model development efforts Drives continuous innovation in modeling efforts including advanced techniques like graph neural networks Develops and mentors junior staff, establishing a culture of R&D to augment the day-to-day aspects of the job What you'll do: Gathers, interprets, and manipulates sophisticated structured and unstructured data to enable sophisticated analytical solutions for the business. Leads and conducts sophisticated analytics demonstrating machine learning, simulation, and optimization to deliver business insights and achieve business objectives. Guides the team selecting the appropriate modeling technique and/or technology with consideration for data limitations, application, and business needs. Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework. Composes and peer reviews technical documents for knowledge persistence, risk management, and technical review audiences. Partners with business leaders from across the organization to proactively identify business needs and propose/recommend analytical and modeling projects to generate business value. Works with business and analytics leaders to prioritize analytics and highly sophisticated modeling problems/research initiatives. Leads efforts to build and maintain a robust library of reusable, production-quality algorithms and supporting code to ensure model development and research efforts are transparent and based on highest-quality data. Assists the team with translating business request(s) into specific analytical questions, implementing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations. Manages project portfolio milestones, risks, and impediments. Anticipates potential issues that could limit project success or implementation and escalates as needed. Establishes and maintains standard methodologies for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards. Interacts with internal and external peers and management to maintain expertise and awareness of leading techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies. Serves as a mentor to data scientists in modeling, analytics, computer science, business acumen, and other interpersonal skills. Participates in enterprise-level efforts to drive the maintenance and transformation of data science technologies and culture. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative field; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree. 8 years of experience in predictive analytics or data analysis 6 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models. 4 years of experience in one or more dynamic scripted languages (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models. Expert ability to write code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency). Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, NoSQL, etc. Strong experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc. Excellent demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics. Proven ability to assess and articulate regulatory implications and expectations of distinct modeling efforts. Project management experience that demonstrates the ability to anticipate and appropriately manage project milestones, risks, and impediments. Demonstrated history of appropriately communicating potential issues that could limit project success or implementation. Expert level experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic models, discriminant analysis, support vector machines, decision trees, and ensemble methods such as Random Forests, XGBoost, LightGBM, and CatBoost. Expert level experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, nearest-neighbors algorithms, DBSCAN, etc. Demonstrated experience in guiding and mentoring junior technical staff in business interactions and model building. Demonstrated ability to communicate ideas with team members and/or business leaders to convey and present very technical information to an audience that may have little or no understanding of technical concepts in data science. A strong track record of communicating results, insights, and technical solutions to senior executive management (or equivalent). Extensive technical skills, consulting experience, and business savvy to collaborate with all levels and subject areas within the organization. What sets you apart: US military experience through military service or a military spouse/domestic partner Graduate degree in a quantitative subject area Over 5 years of experience with model development or other advanced fraud detection algorithms Over 4 years of experience with graph databases and graph solutions Experience in fraud/financial crimes model development Compensation: The salary range for this position is: $164,780 - $314,960. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. . click apply for full job details

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity This role is remote eligible in the continental U.S. with occasional business travel. However, individuals residing within a 60-mile radius of a USAA office will be expected to work on-site four days per week. Relocation assistance is not available for this position. Job Description The Lead Graph Data Scientist - Identity Analytics is responsible for development and implementing quantitative solutions that improve USAA's ability to detect and prevent identity theft, account takeover, and first-party/synthetic fraud. These solutions range from machine learning model development to enterprise deployment of graph analytics capabilities that protect USAA and our Members from these threats. Strong candidates will be able to deliver the following work products and processes: Develop and continuously update internal identity theft and authentication models to mitigate fraud losses and reduce negative member experience from fraud applications, synthetic fraud, and account takeover attempts Closely partner with the Strategy team, Director of Fraud Identity Analytics, Director of Fraud Model Management, and model users on model builds and priorities. Partner with Technology and other key collaborators to deploy a Member Protection graph technology strategy, including vendor selection, business requirements, data needs, and clear use cases spanning financial crimes Deploy graph databases and graph techniques to identify criminal networks engaging in fraud, scams, disputes/claims, and AML, improving fraud detection and loss mitigation Generate and prioritize fraud-dense rings to mitigate losses and improve Member experience Identify and work with technology to integrate new data sources for models and graphs to augment predictive power and improve business performance Exports insights to decision systems to enable better fraud targeting and model development efforts Drives continuous innovation in modeling efforts including advanced techniques like graph neural networks Develops and mentors junior staff, establishing a culture of R&D to augment the day-to-day aspects of the job What you'll do: Gathers, interprets, and manipulates sophisticated structured and unstructured data to enable sophisticated analytical solutions for the business. Leads and conducts sophisticated analytics demonstrating machine learning, simulation, and optimization to deliver business insights and achieve business objectives. Guides the team selecting the appropriate modeling technique and/or technology with consideration for data limitations, application, and business needs. Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework. Composes and peer reviews technical documents for knowledge persistence, risk management, and technical review audiences. Partners with business leaders from across the organization to proactively identify business needs and propose/recommend analytical and modeling projects to generate business value. Works with business and analytics leaders to prioritize analytics and highly sophisticated modeling problems/research initiatives. Leads efforts to build and maintain a robust library of reusable, production-quality algorithms and supporting code to ensure model development and research efforts are transparent and based on highest-quality data. Assists the team with translating business request(s) into specific analytical questions, implementing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations. Manages project portfolio milestones, risks, and impediments. Anticipates potential issues that could limit project success or implementation and escalates as needed. Establishes and maintains standard methodologies for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards. Interacts with internal and external peers and management to maintain expertise and awareness of leading techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies. Serves as a mentor to data scientists in modeling, analytics, computer science, business acumen, and other interpersonal skills. Participates in enterprise-level efforts to drive the maintenance and transformation of data science technologies and culture. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative field; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree. 8 years of experience in predictive analytics or data analysis 6 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models. 4 years of experience in one or more dynamic scripted languages (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models. Expert ability to write code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency). Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, NoSQL, etc. Strong experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc. Excellent demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics. Proven ability to assess and articulate regulatory implications and expectations of distinct modeling efforts. Project management experience that demonstrates the ability to anticipate and appropriately manage project milestones, risks, and impediments. Demonstrated history of appropriately communicating potential issues that could limit project success or implementation. Expert level experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic models, discriminant analysis, support vector machines, decision trees, and ensemble methods such as Random Forests, XGBoost, LightGBM, and CatBoost. Expert level experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, nearest-neighbors algorithms, DBSCAN, etc. Demonstrated experience in guiding and mentoring junior technical staff in business interactions and model building. Demonstrated ability to communicate ideas with team members and/or business leaders to convey and present very technical information to an audience that may have little or no understanding of technical concepts in data science. A strong track record of communicating results, insights, and technical solutions to senior executive management (or equivalent). Extensive technical skills, consulting experience, and business savvy to collaborate with all levels and subject areas within the organization. What sets you apart: US military experience through military service or a military spouse/domestic partner Graduate degree in a quantitative subject area Over 5 years of experience with model development or other advanced fraud detection algorithms Over 4 years of experience with graph databases and graph solutions Experience in fraud/financial crimes model development Compensation: The salary range for this position is: $164,780 - $314,960. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. . click apply for full job details

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity This role is remote eligible in the continental U.S. with occasional business travel. However, individuals residing within a 60-mile radius of a USAA office will be expected to work on-site four days per week. Relocation assistance is not available for this position. Job Description The Lead Graph Data Scientist - Identity Analytics is responsible for development and implementing quantitative solutions that improve USAA's ability to detect and prevent identity theft, account takeover, and first-party/synthetic fraud. These solutions range from machine learning model development to enterprise deployment of graph analytics capabilities that protect USAA and our Members from these threats. Strong candidates will be able to deliver the following work products and processes: Develop and continuously update internal identity theft and authentication models to mitigate fraud losses and reduce negative member experience from fraud applications, synthetic fraud, and account takeover attempts Closely partner with the Strategy team, Director of Fraud Identity Analytics, Director of Fraud Model Management, and model users on model builds and priorities. Partner with Technology and other key collaborators to deploy a Member Protection graph technology strategy, including vendor selection, business requirements, data needs, and clear use cases spanning financial crimes Deploy graph databases and graph techniques to identify criminal networks engaging in fraud, scams, disputes/claims, and AML, improving fraud detection and loss mitigation Generate and prioritize fraud-dense rings to mitigate losses and improve Member experience Identify and work with technology to integrate new data sources for models and graphs to augment predictive power and improve business performance Exports insights to decision systems to enable better fraud targeting and model development efforts Drives continuous innovation in modeling efforts including advanced techniques like graph neural networks Develops and mentors junior staff, establishing a culture of R&D to augment the day-to-day aspects of the job What you'll do: Gathers, interprets, and manipulates sophisticated structured and unstructured data to enable sophisticated analytical solutions for the business. Leads and conducts sophisticated analytics demonstrating machine learning, simulation, and optimization to deliver business insights and achieve business objectives. Guides the team selecting the appropriate modeling technique and/or technology with consideration for data limitations, application, and business needs. Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework. Composes and peer reviews technical documents for knowledge persistence, risk management, and technical review audiences. Partners with business leaders from across the organization to proactively identify business needs and propose/recommend analytical and modeling projects to generate business value. Works with business and analytics leaders to prioritize analytics and highly sophisticated modeling problems/research initiatives. Leads efforts to build and maintain a robust library of reusable, production-quality algorithms and supporting code to ensure model development and research efforts are transparent and based on highest-quality data. Assists the team with translating business request(s) into specific analytical questions, implementing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations. Manages project portfolio milestones, risks, and impediments. Anticipates potential issues that could limit project success or implementation and escalates as needed. Establishes and maintains standard methodologies for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards. Interacts with internal and external peers and management to maintain expertise and awareness of leading techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies. Serves as a mentor to data scientists in modeling, analytics, computer science, business acumen, and other interpersonal skills. Participates in enterprise-level efforts to drive the maintenance and transformation of data science technologies and culture. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative field; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree. 8 years of experience in predictive analytics or data analysis 6 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models. 4 years of experience in one or more dynamic scripted languages (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models. Expert ability to write code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency). Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, NoSQL, etc. Strong experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc. Excellent demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics. Proven ability to assess and articulate regulatory implications and expectations of distinct modeling efforts. Project management experience that demonstrates the ability to anticipate and appropriately manage project milestones, risks, and impediments. Demonstrated history of appropriately communicating potential issues that could limit project success or implementation. Expert level experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic models, discriminant analysis, support vector machines, decision trees, and ensemble methods such as Random Forests, XGBoost, LightGBM, and CatBoost. Expert level experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, nearest-neighbors algorithms, DBSCAN, etc. Demonstrated experience in guiding and mentoring junior technical staff in business interactions and model building. Demonstrated ability to communicate ideas with team members and/or business leaders to convey and present very technical information to an audience that may have little or no understanding of technical concepts in data science. A strong track record of communicating results, insights, and technical solutions to senior executive management (or equivalent). Extensive technical skills, consulting experience, and business savvy to collaborate with all levels and subject areas within the organization. What sets you apart: US military experience through military service or a military spouse/domestic partner Graduate degree in a quantitative subject area Over 5 years of experience with model development or other advanced fraud detection algorithms Over 4 years of experience with graph databases and graph solutions Experience in fraud/financial crimes model development Compensation: The salary range for this position is: $164,780 - $314,960. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. . click apply for full job details

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity This role is remote eligible in the continental U.S. with occasional business travel. However, individuals residing within a 60-mile radius of a USAA office will be expected to work on-site four days per week. Relocation assistance is not available for this position. Job Description The Lead Graph Data Scientist - Identity Analytics is responsible for development and implementing quantitative solutions that improve USAA's ability to detect and prevent identity theft, account takeover, and first-party/synthetic fraud. These solutions range from machine learning model development to enterprise deployment of graph analytics capabilities that protect USAA and our Members from these threats. Strong candidates will be able to deliver the following work products and processes: Develop and continuously update internal identity theft and authentication models to mitigate fraud losses and reduce negative member experience from fraud applications, synthetic fraud, and account takeover attempts Closely partner with the Strategy team, Director of Fraud Identity Analytics, Director of Fraud Model Management, and model users on model builds and priorities. Partner with Technology and other key collaborators to deploy a Member Protection graph technology strategy, including vendor selection, business requirements, data needs, and clear use cases spanning financial crimes Deploy graph databases and graph techniques to identify criminal networks engaging in fraud, scams, disputes/claims, and AML, improving fraud detection and loss mitigation Generate and prioritize fraud-dense rings to mitigate losses and improve Member experience Identify and work with technology to integrate new data sources for models and graphs to augment predictive power and improve business performance Exports insights to decision systems to enable better fraud targeting and model development efforts Drives continuous innovation in modeling efforts including advanced techniques like graph neural networks Develops and mentors junior staff, establishing a culture of R&D to augment the day-to-day aspects of the job What you'll do: Gathers, interprets, and manipulates sophisticated structured and unstructured data to enable sophisticated analytical solutions for the business. Leads and conducts sophisticated analytics demonstrating machine learning, simulation, and optimization to deliver business insights and achieve business objectives. Guides the team selecting the appropriate modeling technique and/or technology with consideration for data limitations, application, and business needs. Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework. Composes and peer reviews technical documents for knowledge persistence, risk management, and technical review audiences. Partners with business leaders from across the organization to proactively identify business needs and propose/recommend analytical and modeling projects to generate business value. Works with business and analytics leaders to prioritize analytics and highly sophisticated modeling problems/research initiatives. Leads efforts to build and maintain a robust library of reusable, production-quality algorithms and supporting code to ensure model development and research efforts are transparent and based on highest-quality data. Assists the team with translating business request(s) into specific analytical questions, implementing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations. Manages project portfolio milestones, risks, and impediments. Anticipates potential issues that could limit project success or implementation and escalates as needed. Establishes and maintains standard methodologies for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards. Interacts with internal and external peers and management to maintain expertise and awareness of leading techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies. Serves as a mentor to data scientists in modeling, analytics, computer science, business acumen, and other interpersonal skills. Participates in enterprise-level efforts to drive the maintenance and transformation of data science technologies and culture. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative field; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree. 8 years of experience in predictive analytics or data analysis 6 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models. 4 years of experience in one or more dynamic scripted languages (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models. Expert ability to write code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency). Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, NoSQL, etc. Strong experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc. Excellent demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics. Proven ability to assess and articulate regulatory implications and expectations of distinct modeling efforts. Project management experience that demonstrates the ability to anticipate and appropriately manage project milestones, risks, and impediments. Demonstrated history of appropriately communicating potential issues that could limit project success or implementation. Expert level experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic models, discriminant analysis, support vector machines, decision trees, and ensemble methods such as Random Forests, XGBoost, LightGBM, and CatBoost. Expert level experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, nearest-neighbors algorithms, DBSCAN, etc. Demonstrated experience in guiding and mentoring junior technical staff in business interactions and model building. Demonstrated ability to communicate ideas with team members and/or business leaders to convey and present very technical information to an audience that may have little or no understanding of technical concepts in data science. A strong track record of communicating results, insights, and technical solutions to senior executive management (or equivalent). Extensive technical skills, consulting experience, and business savvy to collaborate with all levels and subject areas within the organization. What sets you apart: US military experience through military service or a military spouse/domestic partner Graduate degree in a quantitative subject area Over 5 years of experience with model development or other advanced fraud detection algorithms Over 4 years of experience with graph databases and graph solutions Experience in fraud/financial crimes model development Compensation: The salary range for this position is: $164,780 - $314,960. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. . click apply for full job details