USAA
San Antonio, Texas
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 AI Data Solutions Scientist in the Technology organization at USAA, you will work within our innovative Data Science team and collaborate cross-functionally with our architecture, engineering, and product partners to transform our operations and experiences while producing actionable insights to drive our association forward. As a member of our dynamic community of problem-solvers, you will tackle a broad and evolving spectrum of business targets to provide outstanding impacts for our membership through scaled solutions and cloud technologies, leveraging both structured and unstructured data through traditional pillars of operations research such as simulation, optimization, and machine-learning techniques, as well as a heavy emphasis on cutting-edge technologies with generative AI, large/small language models, and advanced agent frameworks. This team is the backbone of the next generation of AI modeling at USAA, and we hope you join us on the frontier! 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, or Phoenix, AZ. Relocation assistance is not available for this position. What you'll do: Gather, interpret, and manipulate structured and unstructured data to enable advanced analytical solutions for the business. Develop scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and business value. Select the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs. Develop and deploy models within the Model Development Control (MDC) and Model Risk Management (MRM) framework. Composes, and assists peers with composing, technical documents for knowledge persistence, risk management, and technical review audiences. Assess business needs to propose/recommend analytical and modeling projects to add business value. Work with business and analytics leaders to prioritize analytics and modeling problems/research efforts. 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 the highest quality data. Translate complex business request(s) into specific analytical questions, executes on the analysis and/or modeling, and then communicates outcomes to non-technical business colleagues with focus on business action and recommendations. Manage project milestones, risks, and impediments. Escalates potential issues that could limit project success or implementation. Develop best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards. Maintain expertise and awareness of cutting-edge techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies. Serve as a mentor to junior data scientists in modeling, analytics, and computer science tasks. Participate in internal communities that drive the maintenance and transformation of data science technologies and culture. Ensure 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, Science, Engineering, or quantitative field; OR 4 years of relevant education and/or experience; and 6+ years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master's, PhD) in mathematics, computer science, statistics, science and engineering, ai, or other similar quantitative discipline and 4+ years of experience in predictive analytics or data analysis. 4+ years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models. 4+ years of experience in Python for performing statical analysis and/or building and scoring AI/ML models Experience writing 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, HQL, NoSQL, etc. Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics and understanding real-world constraints such as latency, cost, and reliability in AI solution designs. Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts across risk stripes, including experience in the documentation and statistical validation of models for risk management. Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc. Advanced experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc. Expertise in LLMs and agentic systems development with frameworks such as LangChain/LangGraph, AgentCore, VertexAI, MCP, or others, with proven experience including prompt engineering, tuning and post-training techniques, multi-agent systems, agent optimization and tool use, RAG and context optimization, and observability and monitoring. MLOps Integration experience in facilitating engineering implementation of production scaled AI solutions in partnership with dedicated AI Engineers in cloud environments such as AWS or GCP. Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results. Experience guiding and mentoring junior technical staff in business interactions and model building. What sets you apart: Financial services, insurance, banking, or other highly regulated industry experience. Experience with cloud-native application development and modernization initiatives. US military experience through military service or a military spouse/domestic partner Compensation range: The salary range for this position is: $143,320 - $273,930. 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 AI Data Solutions Scientist in the Technology organization at USAA, you will work within our innovative Data Science team and collaborate cross-functionally with our architecture, engineering, and product partners to transform our operations and experiences while producing actionable insights to drive our association forward. As a member of our dynamic community of problem-solvers, you will tackle a broad and evolving spectrum of business targets to provide outstanding impacts for our membership through scaled solutions and cloud technologies, leveraging both structured and unstructured data through traditional pillars of operations research such as simulation, optimization, and machine-learning techniques, as well as a heavy emphasis on cutting-edge technologies with generative AI, large/small language models, and advanced agent frameworks. This team is the backbone of the next generation of AI modeling at USAA, and we hope you join us on the frontier! 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, or Phoenix, AZ. Relocation assistance is not available for this position. What you'll do: Gather, interpret, and manipulate structured and unstructured data to enable advanced analytical solutions for the business. Develop scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and business value. Select the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs. Develop and deploy models within the Model Development Control (MDC) and Model Risk Management (MRM) framework. Composes, and assists peers with composing, technical documents for knowledge persistence, risk management, and technical review audiences. Assess business needs to propose/recommend analytical and modeling projects to add business value. Work with business and analytics leaders to prioritize analytics and modeling problems/research efforts. 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 the highest quality data. Translate complex business request(s) into specific analytical questions, executes on the analysis and/or modeling, and then communicates outcomes to non-technical business colleagues with focus on business action and recommendations. Manage project milestones, risks, and impediments. Escalates potential issues that could limit project success or implementation. Develop best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards. Maintain expertise and awareness of cutting-edge techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies. Serve as a mentor to junior data scientists in modeling, analytics, and computer science tasks. Participate in internal communities that drive the maintenance and transformation of data science technologies and culture. Ensure 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, Science, Engineering, or quantitative field; OR 4 years of relevant education and/or experience; and 6+ years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master's, PhD) in mathematics, computer science, statistics, science and engineering, ai, or other similar quantitative discipline and 4+ years of experience in predictive analytics or data analysis. 4+ years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models. 4+ years of experience in Python for performing statical analysis and/or building and scoring AI/ML models Experience writing 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, HQL, NoSQL, etc. Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics and understanding real-world constraints such as latency, cost, and reliability in AI solution designs. Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts across risk stripes, including experience in the documentation and statistical validation of models for risk management. Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc. Advanced experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc. Expertise in LLMs and agentic systems development with frameworks such as LangChain/LangGraph, AgentCore, VertexAI, MCP, or others, with proven experience including prompt engineering, tuning and post-training techniques, multi-agent systems, agent optimization and tool use, RAG and context optimization, and observability and monitoring. MLOps Integration experience in facilitating engineering implementation of production scaled AI solutions in partnership with dedicated AI Engineers in cloud environments such as AWS or GCP. Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results. Experience guiding and mentoring junior technical staff in business interactions and model building. What sets you apart: Financial services, insurance, banking, or other highly regulated industry experience. Experience with cloud-native application development and modernization initiatives. US military experience through military service or a military spouse/domestic partner Compensation range: The salary range for this position is: $143,320 - $273,930. 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.
Vail Resorts
Broomfield, Colorado
Job Description Job Description Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you're ready to pursue your fullest potential, we want to get to know you! Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first). Job Summary: We are looking for a curious, driven, innovative machine learning engineer who takes initiative to solve problems and create environments that accelerate the development, deployment, and usage of data science models and AI to drive greater organizational impact. The Data Science & Data Engineering team within the Enterprise Analytics organization builds data assets, predictive models, analytical applications, and platforms across the organization. Our team collaborates with business stakeholders, analysts, and technology teams to tackle high-impact use cases with state-of-the-art models and tools to grow the business, streamline costs, and improve guest experiences. Job Specifications: Starting Wage: $140,000 - $185,000 + Annual Bonus Employment Type: Year Round Shift Type: Full Time hours Minimum Age: At least 18 years of age Housing Availability: No Job Responsibilities: Productionize ML models developed by data science into reliable, monitored, maintainable systems. Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable. Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows. Identify and scope opportunities for ML engineering across the business for high-impact. Develop reusable tools , libraries, standards, documentation, and production-readiness practices to enable data science and data engineering teams. Develop analytical and model-powered applications that turn data and ML outputs into usable business workflows for end users. Prepare the platform for future AI engineering , including LLM and agent-based systems, as the organization matures. Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews. Job Requirements: Technical Skills: Quantitative Foundation : B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering). Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts. Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services. Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage. ML Lifecycle Fluency: understand the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement. Production ML Patterns: understand core MLOps patterns such as model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback. Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture. Databricks Expertise : You're familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance. DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability. Application Development : You can build applications, APIs, dashboards, or workflow tools that sit on top of data and model outputs. System Design: You can reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use. Soft Skills: Curious : bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning. Ownership : take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions. Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences. Collaboration: work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders. Pragmatism : You know how to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship. Preferred qualifications: A graduate degree (Masters or PhD) in a quantitative field Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management Experience with AI engineer to use, build, and monitor agentic solutions The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors. Job Benefits Ski/Mountain Perks! Free passes for employees, employee discounted lift tickets for friends and family AND free ski lessons MORE employee discounts on lodging, food, gear, and mountain shuttles 401(k) Retirement Plan Employee Assistance Program Excellent training and professional development Full Time roles are eligible for the above, plus: Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours) Free ski passes for dependents Critical Illness and Accident plans Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states in which we currently operate. This includes: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, and Wyoming. Please note that the ability to work in person or off-site, and the particulars related to such work, are subject to change at any time; and, accordingly, the Company reserves the right to change its policies and/or require in-person/in-office work or off-site work at any time in its sole discretion. In completing this application, and when submitting related documentation, applicants may redact information that identifies their age, date of birth, and/or dates of attendance at or graduation from an educational institution. We follow all federal, state, and local laws including restrictions on child/minor labor. Minors hired into this position will not be asked or permitted to engage in any activities restricted to adult workers. Vail Resorts is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other status protected by applicable law. Requisition ID 517322 Reference Date: 09/05/2026 Job Code Function: Data Science
Job Description Job Description Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you're ready to pursue your fullest potential, we want to get to know you! Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first). Job Summary: We are looking for a curious, driven, innovative machine learning engineer who takes initiative to solve problems and create environments that accelerate the development, deployment, and usage of data science models and AI to drive greater organizational impact. The Data Science & Data Engineering team within the Enterprise Analytics organization builds data assets, predictive models, analytical applications, and platforms across the organization. Our team collaborates with business stakeholders, analysts, and technology teams to tackle high-impact use cases with state-of-the-art models and tools to grow the business, streamline costs, and improve guest experiences. Job Specifications: Starting Wage: $140,000 - $185,000 + Annual Bonus Employment Type: Year Round Shift Type: Full Time hours Minimum Age: At least 18 years of age Housing Availability: No Job Responsibilities: Productionize ML models developed by data science into reliable, monitored, maintainable systems. Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable. Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows. Identify and scope opportunities for ML engineering across the business for high-impact. Develop reusable tools , libraries, standards, documentation, and production-readiness practices to enable data science and data engineering teams. Develop analytical and model-powered applications that turn data and ML outputs into usable business workflows for end users. Prepare the platform for future AI engineering , including LLM and agent-based systems, as the organization matures. Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews. Job Requirements: Technical Skills: Quantitative Foundation : B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering). Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts. Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services. Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage. ML Lifecycle Fluency: understand the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement. Production ML Patterns: understand core MLOps patterns such as model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback. Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture. Databricks Expertise : You're familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance. DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability. Application Development : You can build applications, APIs, dashboards, or workflow tools that sit on top of data and model outputs. System Design: You can reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use. Soft Skills: Curious : bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning. Ownership : take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions. Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences. Collaboration: work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders. Pragmatism : You know how to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship. Preferred qualifications: A graduate degree (Masters or PhD) in a quantitative field Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management Experience with AI engineer to use, build, and monitor agentic solutions The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors. Job Benefits Ski/Mountain Perks! Free passes for employees, employee discounted lift tickets for friends and family AND free ski lessons MORE employee discounts on lodging, food, gear, and mountain shuttles 401(k) Retirement Plan Employee Assistance Program Excellent training and professional development Full Time roles are eligible for the above, plus: Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours) Free ski passes for dependents Critical Illness and Accident plans Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states in which we currently operate. This includes: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, and Wyoming. Please note that the ability to work in person or off-site, and the particulars related to such work, are subject to change at any time; and, accordingly, the Company reserves the right to change its policies and/or require in-person/in-office work or off-site work at any time in its sole discretion. In completing this application, and when submitting related documentation, applicants may redact information that identifies their age, date of birth, and/or dates of attendance at or graduation from an educational institution. We follow all federal, state, and local laws including restrictions on child/minor labor. Minors hired into this position will not be asked or permitted to engage in any activities restricted to adult workers. Vail Resorts is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other status protected by applicable law. Requisition ID 517322 Reference Date: 09/05/2026 Job Code Function: Data Science