This job is with Gilead Sciences Inc., an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description As Associate Director, Data Science, you will proactively bring innovative data science techniques and insights to business to drive/support strategic business decisions. You would be responsible for standing up the capability of integrated HCP, patient journey and predictive sciences at scale for commercial market. The person will work closely with integrated insights, commercial ops, patient engagement and omni channel analytics leads. Hands on functional expertise, highly collaborative mindset and leadership skillsets required. This role will report to Sr. Director, Marketing Sciences and based in either Foster City, CA or Parsippany, NJ. Responsibilities: Be a partner in driving the industrialization of predictive sciences to help understand the patient journey and triggers robustly for markets. Understand Gilead's commercial business objectives, develop and deploy scalable data science products and insights to influence decisions in marketing, sales, medical and etc. Lead Data science projects end to end include convert unconstructured business questions into data science solutions, give guidance to offshore, be a hands-on leader who knows how to code and debug, communicate with stakeholders and etc. Foster a culture of measurement and impact and incorporate feedback to continuously improve data science models Bring thought leadership and thorough understanding of statistics, primarily predictive algorithms & methodologies, to construct robust propensity models for impactful commercial use Create data science products that can be refreshed, reproduced and replicated Work with other Data Scientists and Analysts to define retraining schedule and measure propensity models for impact Partner with global teams to cross-pollinate ideas and replicate successful models from other countries and vice versa Excellent communication and ability to abstract backend complexity where it is not needed Manage DS initiatives and deliveries for a priority TA Competencies: Results orientation. The ideal candidate will thrive in a fast-paced, high-growth environment. He/She/They will have a strong drive to meet and exceed goals, even under adverse circumstances, and is willing to take ownership of problems and make decisions in order to move forward. The candidate will be adept at clearly defining objectives and priorities and establishing appropriate milestones through a strong understanding of the market and innovative approaches. He/She/They will assign accountability and incorporate disciplined processes to ensure success and nimbly handle 'derailments' with contingency plans and coordination. Team leadership. The successful candidate will have demonstrated the ability to build, develop, and motivate a team as evidenced by effective hiring, coaching, and mentoring of direct reports. Additionally, this individual will have a track record of successfully leveraging diversity of thought to achieve the highest level of results. The ideal candidate will develop an inclusive culture comfortable with challenging current market paradigms to achieve and exceed goals. He/She/They will also have constructed an appropriate succession plan and process. Strategic Orientation. The successful candidate will be able to articulate evolving priorities for the business, identify market opportunities and adapt short-term plans. This includes the ability to strategically assess customer needs and build/execute specific, segmented strategies to win business across a diverse set of customers. The successful candidate will have passion for, and success in, developing commercial strategies that have measurable business impact. Collaboration and Influence. The qualified candidate must be able to influence without ownership, which they will do by demonstrating competence and confidence, being personally accessible and likable, being a good listener, use fact-based persuasion, passion, and persistence as appropriate to the audience and issue at stake. Gaining the support and involvement of key internal constituencies will be critical to success, as will influencing those important constituencies external to the company. The successful candidate must therefore have excellent skills at influencing outcomes and shaping and catalyzing dialogue across and outside the organization. Credibility and integrity are critical attributes to effectively command the respect and trust of key individuals Basic Qualifications: Bachelor's Degree and Eight Years' Experience OR Masters' Degree and Six Years' Experience OR PhD and Two Years' Experience Preferred Qualifications: Strong working knowledge of machine learning algorithms, including regression, clustering, neural networks, Bayesian models, RNN, CNN, Tree-based algorithms (RF, XGB, LightGBM), SMOTE and etc. Experience in building, implementing and using AI-based solutions with proven business impact Experience working with standard pharma and consumer data types and sources such as patient claims, Xponent, Plantrak, sales, activity. Strong leadership that be able to manage initiatives from beginning to end himself/herself Effective written and verbal communication skills Experience in implementing, optimizing and using AI-based solutions to establish proven business impact Expertise in commonly used pharma datasets such as IQVIA, Symphony, Komodo claims, Optum, Definitive health, Health Verity, EMR/HER Expertise in Python including commonly used data science libraries such as numpy, pandas, scikit-learn, seaborn, networkx, etc. Expertise in data science techniques such ANCOVA, Bayesian Statistics, Econometric modeling, Neural Networks/Logistic, etc. Understanding of cloud-based technologies and tools such as Databricks, S3, etc. Demonstrated product mindset Familiarity with product management principles Effective written and verbal communication skills Strong team player. Inclusive, objective, cross-functional, team member with a positive and solution-oriented mindset Understanding of emerging data science capabilities (fields, methodologies, algorithms, etc.) and potential application in pharma/health care Thorough understanding of datasets including their strengths and limitations such as capture rate, projections and acceptable error ranges for different therapeutic spaces Masters degree in a quantitative field with at least 8 years of relevant data science/analytics experience OR Undergraduate degree in a quantitative field with at least 10 years of relevant data science/analytics experience People Leader Accountabilities: Create Inclusion - knowing the business value of diverse teams, modeling inclusion, and embedding the value of diversity in the way they manage their teams. Develop Talent - understand the skills, experience, aspirations, and potential of their employees and coach them on current performance and future potential. They ensure employees are receiving the feedback and insight needed to grow, develop, and realize their purpose. Empower Teams - connect the team to the organization by aligning goals, purpose, and organizational objectives and holding them to account. They provide the support needed to remove barriers and connect their team to the broader ecosystem. The salary range for this position is: Bay Area: $195,670.00 - $253,220.00. Other US Locations: $177,905.00 - $230,230.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans . For additional benefits information, visit: Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans click apply for full job details
11/13/2026
Full time
This job is with Gilead Sciences Inc., an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description As Associate Director, Data Science, you will proactively bring innovative data science techniques and insights to business to drive/support strategic business decisions. You would be responsible for standing up the capability of integrated HCP, patient journey and predictive sciences at scale for commercial market. The person will work closely with integrated insights, commercial ops, patient engagement and omni channel analytics leads. Hands on functional expertise, highly collaborative mindset and leadership skillsets required. This role will report to Sr. Director, Marketing Sciences and based in either Foster City, CA or Parsippany, NJ. Responsibilities: Be a partner in driving the industrialization of predictive sciences to help understand the patient journey and triggers robustly for markets. Understand Gilead's commercial business objectives, develop and deploy scalable data science products and insights to influence decisions in marketing, sales, medical and etc. Lead Data science projects end to end include convert unconstructured business questions into data science solutions, give guidance to offshore, be a hands-on leader who knows how to code and debug, communicate with stakeholders and etc. Foster a culture of measurement and impact and incorporate feedback to continuously improve data science models Bring thought leadership and thorough understanding of statistics, primarily predictive algorithms & methodologies, to construct robust propensity models for impactful commercial use Create data science products that can be refreshed, reproduced and replicated Work with other Data Scientists and Analysts to define retraining schedule and measure propensity models for impact Partner with global teams to cross-pollinate ideas and replicate successful models from other countries and vice versa Excellent communication and ability to abstract backend complexity where it is not needed Manage DS initiatives and deliveries for a priority TA Competencies: Results orientation. The ideal candidate will thrive in a fast-paced, high-growth environment. He/She/They will have a strong drive to meet and exceed goals, even under adverse circumstances, and is willing to take ownership of problems and make decisions in order to move forward. The candidate will be adept at clearly defining objectives and priorities and establishing appropriate milestones through a strong understanding of the market and innovative approaches. He/She/They will assign accountability and incorporate disciplined processes to ensure success and nimbly handle 'derailments' with contingency plans and coordination. Team leadership. The successful candidate will have demonstrated the ability to build, develop, and motivate a team as evidenced by effective hiring, coaching, and mentoring of direct reports. Additionally, this individual will have a track record of successfully leveraging diversity of thought to achieve the highest level of results. The ideal candidate will develop an inclusive culture comfortable with challenging current market paradigms to achieve and exceed goals. He/She/They will also have constructed an appropriate succession plan and process. Strategic Orientation. The successful candidate will be able to articulate evolving priorities for the business, identify market opportunities and adapt short-term plans. This includes the ability to strategically assess customer needs and build/execute specific, segmented strategies to win business across a diverse set of customers. The successful candidate will have passion for, and success in, developing commercial strategies that have measurable business impact. Collaboration and Influence. The qualified candidate must be able to influence without ownership, which they will do by demonstrating competence and confidence, being personally accessible and likable, being a good listener, use fact-based persuasion, passion, and persistence as appropriate to the audience and issue at stake. Gaining the support and involvement of key internal constituencies will be critical to success, as will influencing those important constituencies external to the company. The successful candidate must therefore have excellent skills at influencing outcomes and shaping and catalyzing dialogue across and outside the organization. Credibility and integrity are critical attributes to effectively command the respect and trust of key individuals Basic Qualifications: Bachelor's Degree and Eight Years' Experience OR Masters' Degree and Six Years' Experience OR PhD and Two Years' Experience Preferred Qualifications: Strong working knowledge of machine learning algorithms, including regression, clustering, neural networks, Bayesian models, RNN, CNN, Tree-based algorithms (RF, XGB, LightGBM), SMOTE and etc. Experience in building, implementing and using AI-based solutions with proven business impact Experience working with standard pharma and consumer data types and sources such as patient claims, Xponent, Plantrak, sales, activity. Strong leadership that be able to manage initiatives from beginning to end himself/herself Effective written and verbal communication skills Experience in implementing, optimizing and using AI-based solutions to establish proven business impact Expertise in commonly used pharma datasets such as IQVIA, Symphony, Komodo claims, Optum, Definitive health, Health Verity, EMR/HER Expertise in Python including commonly used data science libraries such as numpy, pandas, scikit-learn, seaborn, networkx, etc. Expertise in data science techniques such ANCOVA, Bayesian Statistics, Econometric modeling, Neural Networks/Logistic, etc. Understanding of cloud-based technologies and tools such as Databricks, S3, etc. Demonstrated product mindset Familiarity with product management principles Effective written and verbal communication skills Strong team player. Inclusive, objective, cross-functional, team member with a positive and solution-oriented mindset Understanding of emerging data science capabilities (fields, methodologies, algorithms, etc.) and potential application in pharma/health care Thorough understanding of datasets including their strengths and limitations such as capture rate, projections and acceptable error ranges for different therapeutic spaces Masters degree in a quantitative field with at least 8 years of relevant data science/analytics experience OR Undergraduate degree in a quantitative field with at least 10 years of relevant data science/analytics experience People Leader Accountabilities: Create Inclusion - knowing the business value of diverse teams, modeling inclusion, and embedding the value of diversity in the way they manage their teams. Develop Talent - understand the skills, experience, aspirations, and potential of their employees and coach them on current performance and future potential. They ensure employees are receiving the feedback and insight needed to grow, develop, and realize their purpose. Empower Teams - connect the team to the organization by aligning goals, purpose, and organizational objectives and holding them to account. They provide the support needed to remove barriers and connect their team to the broader ecosystem. The salary range for this position is: Bay Area: $195,670.00 - $253,220.00. Other US Locations: $177,905.00 - $230,230.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans . For additional benefits information, visit: Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans click apply for full job details
Serve as the senior hands-on full-stack engineer and architect, turning scientist-built prototypes into reliable, secure, production-ready systems for R&D. Set engineering standards and deployment patterns, build cloud-native applications, and partner with scientists, platform teams, Cyber and Quality on integration and validation. Responsibilities Set engineering standards, architecture, release, incident-response and production-readiness practices for team applications. Refactor and productize prototypes with sound architecture, testing, observability, security, documentation and operability. Build reusable application-to-platform patterns for authentication, secrets, networking, deployment and monitoring. Establish CI/CD pipelines, infrastructure as code, environments, starter templates, monitoring and operational runbooks. Review and approve code, maintain repository merge gates, and conduct design and architecture reviews. Design and build full-stack cloud-native systems, including APIs, workflow services, data and vector stores, identity services and user interfaces. Required Skills Full-stack software development Cloud-native architecture API development CI/CD pipeline engineering Infrastructure as code Application security Authentication and single sign-on Automated testing and regression evaluation Observability and monitoring Vector and data store integration
11/12/2026
Full time
Serve as the senior hands-on full-stack engineer and architect, turning scientist-built prototypes into reliable, secure, production-ready systems for R&D. Set engineering standards and deployment patterns, build cloud-native applications, and partner with scientists, platform teams, Cyber and Quality on integration and validation. Responsibilities Set engineering standards, architecture, release, incident-response and production-readiness practices for team applications. Refactor and productize prototypes with sound architecture, testing, observability, security, documentation and operability. Build reusable application-to-platform patterns for authentication, secrets, networking, deployment and monitoring. Establish CI/CD pipelines, infrastructure as code, environments, starter templates, monitoring and operational runbooks. Review and approve code, maintain repository merge gates, and conduct design and architecture reviews. Design and build full-stack cloud-native systems, including APIs, workflow services, data and vector stores, identity services and user interfaces. Required Skills Full-stack software development Cloud-native architecture API development CI/CD pipeline engineering Infrastructure as code Application security Authentication and single sign-on Automated testing and regression evaluation Observability and monitoring Vector and data store integration
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity . click apply for full job details
11/11/2026
Full time
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity . click apply for full job details
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity . click apply for full job details
11/11/2026
Full time
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity . click apply for full job details
This job is with Novartis, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Summary Novartis has an exciting opportunity for a Director, Analytics Engineering. This role is responsible for building next-generation, AI-powered automated data pipelines and scalable data repositories that enable enterprise data science and analytics at scale. By leveraging advanced AI technologies, modern data engineering tools, and feature engineering platforms, this director creates self-service, analytics-ready datasets and enterprise feature stores that empower both expert data scientists and citizen data scientists to rapidly develop, deploy, and scale models. This position can be based remotely anywhere in the U.S. (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. The expectation of working hours and travel (domestic and/or international) will be defined by the hiring manager. This position will require 20% travel. There are 2 positions available. About the Role Major accountabilities: Design and implement intelligent, self-healing data pipelines that leverage AI/ML for automated data quality monitoring, anomaly detection, and remediation. Build and maintain centralized feature stores that enable feature reusability across multiple models and use cases. Create curated data repositories optimized for data science/AI workflows, including training datasets, evaluation datasets, and production serving layers. Develop automated feature engineering pipelines that transform raw data into analytics-ready features with lineage tracking. Partner with Enterprise IT to optimize analytics platform architecture for high-performance data science workloads. Build automated pipelines that integrate diverse data sources including sales, CRM, patient claims, real-world evidence, and unstructured data. Create self-service data access layers that empower data scientists and analysts to query and extract data independently. Establish SLAs for data availability, freshness, and quality; implement monitoring and observability solutions. Essential Requirements Advanced degree in Computer Science, Data Engineering, or related field; 7+ years of experience in data engineering, ML/AI engineering, or analytics infrastructure. 5+ years leading teams building enterprise-scale data platforms and feature stores. Expert knowledge of feature store technologies (Feast, Tecton, SageMaker Feature Store, Databricks Feature Store). Deep expertise in modern data platforms optimized for ML workloads (Databricks, Auto ML, Snowflake, BigQuery). Strong proficiency in Python, SQL, Spark/PySpark for large-scale data processing. Experience with data orchestration tools (Airflow, Prefect, dbt) and CI/CD for data pipelines. Understanding of data governance, privacy (HIPAA, GDPR), and compliance in life sciences. Preferred Qualities Proven track record of implementing AI/ML-powered automation in data engineering workflows. Strategic thinker who can balance innovation (cutting-edge AI tools) with reliability (production stability). Builder mindset with ability to create scalable, self-service capabilities that reduce dependency on data engineering. Experience in pharmaceutical, healthcare, or life sciences industry. Knowledge of streaming technologies, MLOps tools, and data lakehouse architecture. Novartis Compensation Summary: The salary for this position is expected to range between $194,600 and $361,400 per year. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors. Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards. US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves. To learn more about the culture, rewards and benefits we offer our people click here . Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients' lives. Ready to create a brighter future together? Benefits and Rewards: Learn about all the ways we'll help you thrive personally and professionally. Read our handbook (PDF 30 MB) EEO Statement: The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. Accessibility & Reasonable Accommodations The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to email protected or call + and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
11/10/2026
Full time
This job is with Novartis, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Summary Novartis has an exciting opportunity for a Director, Analytics Engineering. This role is responsible for building next-generation, AI-powered automated data pipelines and scalable data repositories that enable enterprise data science and analytics at scale. By leveraging advanced AI technologies, modern data engineering tools, and feature engineering platforms, this director creates self-service, analytics-ready datasets and enterprise feature stores that empower both expert data scientists and citizen data scientists to rapidly develop, deploy, and scale models. This position can be based remotely anywhere in the U.S. (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. The expectation of working hours and travel (domestic and/or international) will be defined by the hiring manager. This position will require 20% travel. There are 2 positions available. About the Role Major accountabilities: Design and implement intelligent, self-healing data pipelines that leverage AI/ML for automated data quality monitoring, anomaly detection, and remediation. Build and maintain centralized feature stores that enable feature reusability across multiple models and use cases. Create curated data repositories optimized for data science/AI workflows, including training datasets, evaluation datasets, and production serving layers. Develop automated feature engineering pipelines that transform raw data into analytics-ready features with lineage tracking. Partner with Enterprise IT to optimize analytics platform architecture for high-performance data science workloads. Build automated pipelines that integrate diverse data sources including sales, CRM, patient claims, real-world evidence, and unstructured data. Create self-service data access layers that empower data scientists and analysts to query and extract data independently. Establish SLAs for data availability, freshness, and quality; implement monitoring and observability solutions. Essential Requirements Advanced degree in Computer Science, Data Engineering, or related field; 7+ years of experience in data engineering, ML/AI engineering, or analytics infrastructure. 5+ years leading teams building enterprise-scale data platforms and feature stores. Expert knowledge of feature store technologies (Feast, Tecton, SageMaker Feature Store, Databricks Feature Store). Deep expertise in modern data platforms optimized for ML workloads (Databricks, Auto ML, Snowflake, BigQuery). Strong proficiency in Python, SQL, Spark/PySpark for large-scale data processing. Experience with data orchestration tools (Airflow, Prefect, dbt) and CI/CD for data pipelines. Understanding of data governance, privacy (HIPAA, GDPR), and compliance in life sciences. Preferred Qualities Proven track record of implementing AI/ML-powered automation in data engineering workflows. Strategic thinker who can balance innovation (cutting-edge AI tools) with reliability (production stability). Builder mindset with ability to create scalable, self-service capabilities that reduce dependency on data engineering. Experience in pharmaceutical, healthcare, or life sciences industry. Knowledge of streaming technologies, MLOps tools, and data lakehouse architecture. Novartis Compensation Summary: The salary for this position is expected to range between $194,600 and $361,400 per year. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors. Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards. US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves. To learn more about the culture, rewards and benefits we offer our people click here . Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients' lives. Ready to create a brighter future together? Benefits and Rewards: Learn about all the ways we'll help you thrive personally and professionally. Read our handbook (PDF 30 MB) EEO Statement: The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. Accessibility & Reasonable Accommodations The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to email protected or call + and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
Avanos Medical seeks an Associate Director IT Global Data Analytics, Innovation & Digital Experimentation to lead data strategy across our global medtech business. In this role, you will define and deliver advanced analytics, AI/ML, and data engineering solutions that optimize clinical, commercial, and operational decisions. You will own the data experimentation roadmap, partner with business and clinical leaders to identify high value use cases, and oversee end to end project delivery. Responsibilities include managing a technical team, governing data platforms, ensuring data quality, and championing innovation while maintaining security, privacy, and regulatory compliance in a patient-focused environment. Responsibilities Lead global data analytics and digital experimentation strategy for Avanos Medical Identify, prioritize, and deliver high-value analytics and AI/ML use cases across business functions Oversee design and implementation of data platforms, pipelines, and governance frameworks Manage and mentor a technical team of data engineers, scientists, and analysts Ensure data quality, integrity, security, and regulatory compliance in a healthcare context Partner with clinical, commercial, and operations leaders to translate needs into technical solutions Drive experimentation frameworks (A/B testing, pilots, POCs) to validate data-driven initiatives Report performance, insights, and ROI of analytics programs to senior leadership Collaborate with IT and cybersecurity to maintain resilient, scalable data infrastructure Champion a culture of innovation, continuous improvement, and patient-focused decision-making Required Skills Data analytics strategy Data engineering (ETL/ELT, data pipelines) Cloud data platforms (AWS, Azure, or GCP) SQL and relational databases Python or R for analytics and data science Machine learning and AI concepts BI and data visualization tools (Tableau, Power BI, etc.) A/B testing and experimentation frameworks Data governance, security, and privacy (including healthcare context) Project and stakeholder management Statistical analysis and modeling Data architecture and warehousing
11/01/2026
Full time
Avanos Medical seeks an Associate Director IT Global Data Analytics, Innovation & Digital Experimentation to lead data strategy across our global medtech business. In this role, you will define and deliver advanced analytics, AI/ML, and data engineering solutions that optimize clinical, commercial, and operational decisions. You will own the data experimentation roadmap, partner with business and clinical leaders to identify high value use cases, and oversee end to end project delivery. Responsibilities include managing a technical team, governing data platforms, ensuring data quality, and championing innovation while maintaining security, privacy, and regulatory compliance in a patient-focused environment. Responsibilities Lead global data analytics and digital experimentation strategy for Avanos Medical Identify, prioritize, and deliver high-value analytics and AI/ML use cases across business functions Oversee design and implementation of data platforms, pipelines, and governance frameworks Manage and mentor a technical team of data engineers, scientists, and analysts Ensure data quality, integrity, security, and regulatory compliance in a healthcare context Partner with clinical, commercial, and operations leaders to translate needs into technical solutions Drive experimentation frameworks (A/B testing, pilots, POCs) to validate data-driven initiatives Report performance, insights, and ROI of analytics programs to senior leadership Collaborate with IT and cybersecurity to maintain resilient, scalable data infrastructure Champion a culture of innovation, continuous improvement, and patient-focused decision-making Required Skills Data analytics strategy Data engineering (ETL/ELT, data pipelines) Cloud data platforms (AWS, Azure, or GCP) SQL and relational databases Python or R for analytics and data science Machine learning and AI concepts BI and data visualization tools (Tableau, Power BI, etc.) A/B testing and experimentation frameworks Data governance, security, and privacy (including healthcare context) Project and stakeholder management Statistical analysis and modeling Data architecture and warehousing
Lead vehicle pricing strategy at CarMax by developing and operationalizing AI and optimization models that value vehicles across retail sales, customer appraisals, or auction purchases. Manage a team of data scientists, guide cross-functional model implementation, and monitor pricing performance as market conditions change. Responsibilities Develop pricing strategies that support short- and long-term business objectives. Lead development of optimization and pricing models for vehicle valuation. Manage, coach, and set goals for a team of data scientists. Partner with product, technology, and field teams to deploy pricing models. Design experiments to measure the business impact of pricing changes. Monitor model performance, respond to market changes, and resolve pricing system issues. Required Skills Data science Machine learning Python Pricing optimization Statistical modeling Mathematical modeling Experiment design A/B testing Algorithm development Model monitoring
10/31/2026
Full time
Lead vehicle pricing strategy at CarMax by developing and operationalizing AI and optimization models that value vehicles across retail sales, customer appraisals, or auction purchases. Manage a team of data scientists, guide cross-functional model implementation, and monitor pricing performance as market conditions change. Responsibilities Develop pricing strategies that support short- and long-term business objectives. Lead development of optimization and pricing models for vehicle valuation. Manage, coach, and set goals for a team of data scientists. Partner with product, technology, and field teams to deploy pricing models. Design experiments to measure the business impact of pricing changes. Monitor model performance, respond to market changes, and resolve pricing system issues. Required Skills Data science Machine learning Python Pricing optimization Statistical modeling Mathematical modeling Experiment design A/B testing Algorithm development Model monitoring
Job Description Job Description Overview: We are seeking a Lead Systems Specialist to support the Pilot Bioproduction Facility (PBF) at the Walter Reed Army Institute of Research (WRAIR) in Silver Spring, Maryland. PBF is a one-of-a-kind cGMP-compliant pharmaceutical manufacturing facility engaging in next-generation development for cutting-edge companies and government agencies. The professionals at PBF are engaging in trailblazing endeavors every day. Most exciting, the end products vary, so every year brings multiple opportunities for professional enrichment in original projects. CAMRIS International, LLC, is a dynamic medical research and development firm that achieves innovative solutions to health and development challenges through high-quality, cost-effective programs and research management services. We combine our proven systems with today's most effective, evidence-based best practices. Our core practice areas include vaccine research, development, and production; microbiology and infectious disease research; biodefense; clinical research; global health security; and HIV/AIDS programs. Our employees enjoy a collegial environment where individual contributions matter at all levels. At CAMRIS, you will notably improve the lives of people at home and abroad. Responsibilities: Lead data integrity tasks including set up of testing workflows, configuring user access controls, integrating peripherals, setting automated schedules, managing alarms and general software administration tasks. Support cross-Functional teams acting as the main bridge between bench scientists, quality assurance (QA), and IT infrastructure teams. Collaborate with process engineers, scientists, operators, maintenance personnel, and vendors to identify opportunities for automation improvements and operational efficiencies. Communicate effectively, efficiently, and persistently with internal and external stakeholders including WRAIR Information Management Division, the PBF director and CAMRIS staff) Configure, maintain, troubleshoot, and optimize automation and control systems, including PLCs, machine to machine interfaces, and process data backups. Lead automation system design, implementation, commissioning, qualification, operation, and lifecycle management activities. Compliance & Validation: Ensuring data integrity, maintaining audit trails, and supporting GxP or regulatory standards (such as ISO/EPA guidelines). Assist WRAIR Information Management Division (IMD) and PBF end users with troubleshooting and upgrading applications supporting resolution of technical snags, data migrations, writing custom scripts or reports (e.g., LabVantage, Crystal Reports OSIsoft Pi), and managing data integrity through system upgrades. Coordinate with lab personnel to map out testing processes, perform market research, develop user requirement specifications (URS), and review associated software design specifications or functional specifications, as necessary. Develop and maintain system documentation including user requirements specifications (URS), functional specifications, control narratives, configuration details, password management, and backup protocols. Participate in commissioning, startup, and qualification activities including factory acceptance testing (FAT), site acceptance testing (SAT), installation qualification (IQ), operational qualification (OQ), and performance qualification (PQ). Establish software training for end users coordinating with operations, quality and quality assurance teams including authoring SOPs, creating training resources, and leading classroom training sessions at PBF. Lead the setup, configuration, and daily support of LabVantage modules at PBF. Ensure systems meet regulatory standards like GxP, 21 CFR Part 11, and data integrity (ALCOA+) principles. Support GMP manufacturing activities through adherence to quality systems, change management processes, deviation investigations, and corrective and preventive actions (CAPA). Design, implement and document the connections between the LIMS and lab equipment, chromatography data systems, and/or middleware. Compliance & Validation: Ensure systems meet regulatory standards like GxP, 21 CFR Part 11, and data integrity (ALCOA+) principles. Support engineering facilities, calibrations oversight, and shutdown execution at PBF as required. All other duties as required by the supervisor, manager, or program leadership. Qualifications: A Bachelor's degree in Engineering, Computer Science, Information Systems, Chemistry, Biology, or a related scientific/technical field. Understanding of GMP manufacturing practices and regulated computerized systems including data integrity and Good Automated Manufacturing Practice (GAMP) and ICH Q9 (Quality Risk Management). 5+ years working within R&D, MSAT or GMP environments supporting enterprise software or laboratory informatics, with firsthand LIMS administration and/or process automation experience. Experience with PLCs, DCS, SCADA, HMI systems, instrumentation, and industrial communication frameworks such as OPC-UA. Strong background in SQL, data analysis, and understanding of lab and clean core (manufacturing) workflows. Demonstrated oral and written communication with the ability to translate complex lab procedures into logical software requirements using flow-charts, presentations, and good engineering documentation. Experience managing subcontracted integration resources. Preferred Qualifications Familiarity with SQL databases, OSIsoft, and slocal application data stores associated with research, quality control, and manufacturing equipment. Data processing skills using R, python, Microsoft Excel, JMP and OSIsoft PI for quality control charting and multifactorial analysis. AKTA Unicorn method programing and configuration experience. Physical Requirements, Workplace Hazards and Conditions, and PPE and Chemical Requirements The physical requirements, workplace hazards and conditions, and PPE and chemical requirements described here are representative of those that a candidate must meet to perform the essential functions of this job. Reasonable accommodation may be provided to enable individuals with disabilities to perform essential job functions. Physical Demands Occasionally conduct sedentary work that primarily involves sitting/standing. Occasionally conduct light work that includes moving objects up to 20 pounds. Rarely conduct medium work that includes moving objects up to 50 pounds. Rarely conduct heavy work that includes moving objects up to 100 pounds. Rarely conduct very heavy work that includes moving objects over 100 pounds. Occasionally push or pull less than 25 pounds. Rarely push or pull 25 - 45 pounds. Rarely push or pull more than 45 pounds. Rarely reach above shoulder level. Constantly use both hands. Occasionally stand or walk for more than 25 minutes. Occasionally bend, reach, or twist repeatedly. Occasionally kneel, squat, or stoop. Rarely crawl or climb. Occasionally have clear vision (near and/or far), depth perception, peripheral vision, and/or visual acuity. Physical Activities Rarely ascend or descend ladders, stairs, scaffolding, ramps, poles, and the like. Rarely move self in different positions to accomplish tasks in various environments, including tight and confined spaces. Occasionally move about to accomplish tasks or move from one worksite to another. Constantly communicate with others to exchange information. Constantly assess the accuracy, neatness, and thoroughness of the work assigned. Environmental Conditions Occasionally work in low temperatures. Occasionally work in high temperatures. Rarely work in outdoor elements, such as precipitation and wind. Occasionally work in noisy environments. Rarely work in small and/or enclosed spaces. PPE and Chemical Requirements Occasionally wear PPE, including but not limited to gloves, face shields/goggles, safety glasses, and safety shoes. Occasionally wear a lab coat. Rarely wear earplugs/muffs. Occasionally work in a Clean Room Uniform. Occasionally wear a disposable dust/surgical mask. Rarely wear a respirator, such as a disposable respirator mask (N-95), half-face/full-face style, PAPR, SCUBA. Other: Sitting/standing should be managed. Extended screen time is expected. Please submit your resume online at . CAMRIS is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, disability status, or any other characteristic protected by any applicable federal, state, or local law. CAMRIS offers a comprehensive benefits package, including medical, dental, and vision insurance for individuals and families, FSAs, HSA, life and AD&D insurance, short- and long-term disability, legal services, voluntary hospital indemnity, critical illness and accident insurances, EAP, pet insurance, 401(k) with employer match and Roth option, tuition and professional reimbursement, public transportation support in the DMV area, a referral bonus program, vacation with tenure-based increases, PTO, 11 paid holidays . click apply for full job details
09/27/2026
Full time
Job Description Job Description Overview: We are seeking a Lead Systems Specialist to support the Pilot Bioproduction Facility (PBF) at the Walter Reed Army Institute of Research (WRAIR) in Silver Spring, Maryland. PBF is a one-of-a-kind cGMP-compliant pharmaceutical manufacturing facility engaging in next-generation development for cutting-edge companies and government agencies. The professionals at PBF are engaging in trailblazing endeavors every day. Most exciting, the end products vary, so every year brings multiple opportunities for professional enrichment in original projects. CAMRIS International, LLC, is a dynamic medical research and development firm that achieves innovative solutions to health and development challenges through high-quality, cost-effective programs and research management services. We combine our proven systems with today's most effective, evidence-based best practices. Our core practice areas include vaccine research, development, and production; microbiology and infectious disease research; biodefense; clinical research; global health security; and HIV/AIDS programs. Our employees enjoy a collegial environment where individual contributions matter at all levels. At CAMRIS, you will notably improve the lives of people at home and abroad. Responsibilities: Lead data integrity tasks including set up of testing workflows, configuring user access controls, integrating peripherals, setting automated schedules, managing alarms and general software administration tasks. Support cross-Functional teams acting as the main bridge between bench scientists, quality assurance (QA), and IT infrastructure teams. Collaborate with process engineers, scientists, operators, maintenance personnel, and vendors to identify opportunities for automation improvements and operational efficiencies. Communicate effectively, efficiently, and persistently with internal and external stakeholders including WRAIR Information Management Division, the PBF director and CAMRIS staff) Configure, maintain, troubleshoot, and optimize automation and control systems, including PLCs, machine to machine interfaces, and process data backups. Lead automation system design, implementation, commissioning, qualification, operation, and lifecycle management activities. Compliance & Validation: Ensuring data integrity, maintaining audit trails, and supporting GxP or regulatory standards (such as ISO/EPA guidelines). Assist WRAIR Information Management Division (IMD) and PBF end users with troubleshooting and upgrading applications supporting resolution of technical snags, data migrations, writing custom scripts or reports (e.g., LabVantage, Crystal Reports OSIsoft Pi), and managing data integrity through system upgrades. Coordinate with lab personnel to map out testing processes, perform market research, develop user requirement specifications (URS), and review associated software design specifications or functional specifications, as necessary. Develop and maintain system documentation including user requirements specifications (URS), functional specifications, control narratives, configuration details, password management, and backup protocols. Participate in commissioning, startup, and qualification activities including factory acceptance testing (FAT), site acceptance testing (SAT), installation qualification (IQ), operational qualification (OQ), and performance qualification (PQ). Establish software training for end users coordinating with operations, quality and quality assurance teams including authoring SOPs, creating training resources, and leading classroom training sessions at PBF. Lead the setup, configuration, and daily support of LabVantage modules at PBF. Ensure systems meet regulatory standards like GxP, 21 CFR Part 11, and data integrity (ALCOA+) principles. Support GMP manufacturing activities through adherence to quality systems, change management processes, deviation investigations, and corrective and preventive actions (CAPA). Design, implement and document the connections between the LIMS and lab equipment, chromatography data systems, and/or middleware. Compliance & Validation: Ensure systems meet regulatory standards like GxP, 21 CFR Part 11, and data integrity (ALCOA+) principles. Support engineering facilities, calibrations oversight, and shutdown execution at PBF as required. All other duties as required by the supervisor, manager, or program leadership. Qualifications: A Bachelor's degree in Engineering, Computer Science, Information Systems, Chemistry, Biology, or a related scientific/technical field. Understanding of GMP manufacturing practices and regulated computerized systems including data integrity and Good Automated Manufacturing Practice (GAMP) and ICH Q9 (Quality Risk Management). 5+ years working within R&D, MSAT or GMP environments supporting enterprise software or laboratory informatics, with firsthand LIMS administration and/or process automation experience. Experience with PLCs, DCS, SCADA, HMI systems, instrumentation, and industrial communication frameworks such as OPC-UA. Strong background in SQL, data analysis, and understanding of lab and clean core (manufacturing) workflows. Demonstrated oral and written communication with the ability to translate complex lab procedures into logical software requirements using flow-charts, presentations, and good engineering documentation. Experience managing subcontracted integration resources. Preferred Qualifications Familiarity with SQL databases, OSIsoft, and slocal application data stores associated with research, quality control, and manufacturing equipment. Data processing skills using R, python, Microsoft Excel, JMP and OSIsoft PI for quality control charting and multifactorial analysis. AKTA Unicorn method programing and configuration experience. Physical Requirements, Workplace Hazards and Conditions, and PPE and Chemical Requirements The physical requirements, workplace hazards and conditions, and PPE and chemical requirements described here are representative of those that a candidate must meet to perform the essential functions of this job. Reasonable accommodation may be provided to enable individuals with disabilities to perform essential job functions. Physical Demands Occasionally conduct sedentary work that primarily involves sitting/standing. Occasionally conduct light work that includes moving objects up to 20 pounds. Rarely conduct medium work that includes moving objects up to 50 pounds. Rarely conduct heavy work that includes moving objects up to 100 pounds. Rarely conduct very heavy work that includes moving objects over 100 pounds. Occasionally push or pull less than 25 pounds. Rarely push or pull 25 - 45 pounds. Rarely push or pull more than 45 pounds. Rarely reach above shoulder level. Constantly use both hands. Occasionally stand or walk for more than 25 minutes. Occasionally bend, reach, or twist repeatedly. Occasionally kneel, squat, or stoop. Rarely crawl or climb. Occasionally have clear vision (near and/or far), depth perception, peripheral vision, and/or visual acuity. Physical Activities Rarely ascend or descend ladders, stairs, scaffolding, ramps, poles, and the like. Rarely move self in different positions to accomplish tasks in various environments, including tight and confined spaces. Occasionally move about to accomplish tasks or move from one worksite to another. Constantly communicate with others to exchange information. Constantly assess the accuracy, neatness, and thoroughness of the work assigned. Environmental Conditions Occasionally work in low temperatures. Occasionally work in high temperatures. Rarely work in outdoor elements, such as precipitation and wind. Occasionally work in noisy environments. Rarely work in small and/or enclosed spaces. PPE and Chemical Requirements Occasionally wear PPE, including but not limited to gloves, face shields/goggles, safety glasses, and safety shoes. Occasionally wear a lab coat. Rarely wear earplugs/muffs. Occasionally work in a Clean Room Uniform. Occasionally wear a disposable dust/surgical mask. Rarely wear a respirator, such as a disposable respirator mask (N-95), half-face/full-face style, PAPR, SCUBA. Other: Sitting/standing should be managed. Extended screen time is expected. Please submit your resume online at . CAMRIS is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, disability status, or any other characteristic protected by any applicable federal, state, or local law. CAMRIS offers a comprehensive benefits package, including medical, dental, and vision insurance for individuals and families, FSAs, HSA, life and AD&D insurance, short- and long-term disability, legal services, voluntary hospital indemnity, critical illness and accident insurances, EAP, pet insurance, 401(k) with employer match and Roth option, tuition and professional reimbursement, public transportation support in the DMV area, a referral bonus program, vacation with tenure-based increases, PTO, 11 paid holidays . click apply for full job details
