Innovation, Data & Analytics Team, Senior Manager, Data Scientist Full-time

Senior Manager, Data Scientist

The Senior Manager, Data Scientist supports the Innovation, Data & Analytics (IDA) Team by designing and applying advanced analytical methods that enable scalable, AI-enabled workflows and data-informed decision-making across Medical Affairs. The role provides analytical leadership for model selection, cohort and segmentation methodology, evaluation frameworks, and decision logic, working in close partnership with data engineering, architecture, AI/ML engineering, governance, and business stakeholders.

This role combines hands-on data science expertise with project leadership and cross-functional influence. The Senior Manager translates complex medical and business questions into defensible analytical approaches, communicates findings and trade-offs clearly, and helps improve the quality, adoption, and impact of IDA solutions.

Methodology and Analytical Direction

• Lead the selection, design, and evaluation of analytical and machine-learning approaches for IDA initiatives and AI-enabled workflows.

• Design cohort, customer, and healthcare professional segmentation methodologies using appropriate healthcare and real-world data sources.

• Define analytical logic, performance measures, validation methods, and decision criteria for models and agentic workflows.

• Conduct advanced analyses to identify patterns, trends, opportunities, and risks that can inform Medical Affairs priorities and decisions.

• Ensure analytical methods, assumptions, limitations, and outputs are well documented, reproducible, and fit for purpose.

• Evaluate emerging data-science, artificial-intelligence, and large-language-model techniques for relevance, rigor, scalability, and responsible use.

Data, Model, and Solution Development

• Prepare, integrate, explore, and analyze complex structured and unstructured datasets from multiple sources.

• Develop, test, validate, and refine statistical, machine-learning, natural-language-processing, and AI-based models.

• Partner with AI/ML engineers and data engineers to translate analytical methods into reliable, production-ready pipelines and workflows.

• Collaborate with data architecture and governance partners to ensure analytical outputs align with data models, quality standards, privacy requirements, and governance expectations.

• Establish monitoring approaches to assess model performance, data drift, output quality, bias, and continued fitness for use.

• Identify and address data-quality, methodology, or implementation issues that could affect analytical reliability.

Strategic Support and Collaboration

• Provide analytical input to IDA strategic and tactical planning, use-case prioritization, roadmaps, and delivery decisions.

• Translate Medical Affairs and business needs into clear analytical questions, requirements, hypotheses, and evaluation plans.

• Communicate analytical findings, recommendations, uncertainty, and trade-offs clearly to technical and nontechnical stakeholders.

• Partner across IDA and Medical Affairs to ensure solutions are relevant, usable, compliant, and aligned with priority business outcomes.

• Proactively identify new data sources, analytical techniques, and opportunities to improve solution quality, efficiency, and adoption.

• Lead defined projects or analytical workstreams through influence, sound judgment, and effective stakeholder engagement.

Leadership and Capability Building

• Provide technical guidance, mentorship, and coaching to data scientists and other analytical colleagues.

• Promote consistent data-science standards, reusable methods, peer review, documentation, and knowledge sharing across the IDA Team.

• Contribute to an inclusive, collaborative, and change-agile team environment.

• Role-model Pfizer values and behaviors while supporting responsible, transparent, and accountable use of data and AI.

Basic Qualifications

Candidate demonstrates a breadth of diverse capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of external stakeholders to achieve meaningful outcomes and create business impact.

• Bachelor's degree in Data Science, Statistics, Biostatistics, Computer Science, Clinical Informatics, Engineering, or a related quantitative discipline, with 6+ relevant experience; an advanced degree may substitute for a portion of the experience requirement; MBA with 5+ years
• Experience applying data-science methods in healthcare, pharmaceutical, life-sciences, or another regulated environment
• Hands-on experience developing and evaluating statistical, machine-learning, natural-language-processing, or AI-based solutions.
• Proficiency with Python or R and SQL, together with experience using modern data-science libraries and analytical development environments.
• Experience working with healthcare or pharmaceutical data, such as claims, electronic health records, clinical, scientific, engagement, or real-world data.
• Experience defining evaluation frameworks, validating models, and clearly documenting methods, assumptions, limitations, and results.
• Demonstrated ability to independently lead projects or analytical workstreams and influence outcomes in a cross-functional matrixed environment.
• Strong communication and interpersonal skills, with the ability to build credibility and explain complex analytical topics to varied audiences.
• Understanding of data privacy, governance, security, legal, regulatory, and compliance considerations relevant to healthcare analytics and AI.
• Effective English verbal and written communication skills appropriate for scientific, technical, regulatory, and business settings.

Preferred Qualifications

• Master's degree or doctorate in Data Science, Statistics, Biostatistics, Computer Science, Clinical Informatics, or a related field.
• Experience with large language models, generative AI, agentic systems, or the evaluation of AI-enabled workflows.
• Experience with cloud data and analytics platforms such as Databricks, Snowflake, or comparable technologies.
• Familiarity with healthcare data standards or frameworks such as Observational Medical Outcomes Partnership (OMOP) or Healthcare Effectiveness Data and Information Set (HEDIS).
• Experience operationalizing models in partnership with engineering teams and monitoring model performance after deployment.
• Experience mentoring data scientists or providing technical leadership without necessarily having direct reports.
• Working knowledge of pharmaceutical medicine, clinical development, evidence generation, Medical Affairs, and Good Clinical Practice.

Other Job Details:

• Last Date to Apply for Job: September 23rd, 2026.
• Locations: NYHQ or PA-Collegeville or MA-Cambridge or CT-Groton or Europe any Pfizer site or QC – Montreal
• NOT Eligible for Relocation Package
• Position is hybrid and will require to work 2 to 3 days per week on site