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# Innovation, Data & Analytics Team, Senior Manager, Data Scientist

- **Company:** Pfizer Inc.
- **Location:** Cambridge, MA, United States
- **Experience:** Expert
- **Salary:** $124,400.0 - $207,400.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Health Informatics, Cloud Database, Data Architecture, Healthcare Effectiveness Data and Information Set, Python (Programming Language), Machine Learning, SQL Databases, Unstructured Data, Large Language Models, Snowflake, Multi-Agent Systems, Model Validation, Electronic Medical Records, Generative AI, Information Technology, Data Analytics, Health Level Seven International, Databricks
- **Published:** September 12, 2026
- **Apply:** https://www.nexxt.com/job.asp?id=3387100975&tx=KJ7979FFQ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

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., * 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.

## Description

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.


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