Senior Data Scientist — AI-Driven Health Analytics Leader

Biopharma Careers; New York (NY); Hybrid; USD 163,000 - 272,000; Full time

Benefits offered by this job

401(k) match

Retirement savings program

Health benefits

Job summary

Pfizer seeks a senior data science leader to own analytical methodologies and evaluation rigor for AI-based workflows within Innovation, Data & Analytics. You will direct model selection, segmentation science, and agent decision logic in partnership with Engineering and Governance, ensuring rigor and defensibility.

The role collaborates with AI/ML engineers, data architects, and stakeholders across functions to translate methodology into production-grade pipelines, drive adoption, and mentor

Qualifications

• Breadth of leadership capabilities including mentoring and cross-functional influence.
• Advanced degree in data science, statistics, biostatistics, CS, or equivalent.
• 8+ years in data science in healthcare; pharma data experience incl. claims, EHR, and HEDIS/OMOP.

Responsibilities

• Own model selection and evaluation frameworks for AI-based workflows.
• Design segmentation methodology using real-world data sources.
• Direct analytical logic behind agentic workflows for rigor and defensibility.
• Partner with AI/ML Engineer to translate methodology into production-grade agents and pipelines.
• Support strategic planning and collaborative prioritization of medical/analytical initiatives.
• Communicate insights and trade-offs clearly to business and tech stakeholders.
• Mentor junior data scientists and data engineering colleagues.

Skills

Leadership

Data Science

Healthcare Analytics

LLMs

Education

Advanced degree in Data Science / Statistics / Biostatistics

Tools

LLMs

Production-grade pipelines

Job description

Pfizer seeks a senior data science leader to own analytical methodologies and evaluation rigor for AI-based workflows within Innovation, Data & Analytics. You will direct model selection, segmentation science, and agent decision logic in partnership with Engineering and Governance, ensuring rigor and defensibility.

The role collaborates with AI/ML engineers, data architects, and stakeholders across functions to translate methodology into production-grade pipelines, drive adoption, and mentor