Senior Lead, Real-World Data Strategy & AI

Bristol Myers Squibb

Lawrence Township (NJ)

On-site

USD 139,000 - 169,000

Full time

14 days+
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Benefits offered by this job

Health Coverage
Wellbeing Support
Paid Time Off

Job summary

Bristol Myers Squibb is seeking a Senior Manager, Real-World Data Strategy to drive end-to-end RWD initiatives and AI-enabled data solutions. You will lead data product development, governance, and partnerships across R&D, HEOR, and analytics to accelerate insights that improve patient outcomes.

The role requires 4–5 years in data/analytics with hands-on experience in RWD sources and strong cross-functional collaboration.

Qualifications

  • Bachelor's degree in life sciences, data/analytics, epidemiology, public health, or related field.
  • Master's degree preferred (MPH, MBA, Biostatistics, Data Science).
  • 4–5 years in data/analytics/real-world evidence or related field.
  • Hands-on experience with RWD sources (claims, EHR, biomarker, imaging).

Responsibilities

  • Lead end-to-end RWD initiative execution with milestones, owners and risk mitigation.
  • Pilot and embed AI/ML tools and automation into RWD workflows and data pipelines.
  • Evaluate and onboard external RWD sources; design scalable data products.
  • Define KPIs and uphold data governance, metadata and quality standards.

Skills

Strong execution
Clear communicator
Collaborative
Ability to handle ambiguity
AI capability daily use

Education

Bachelor's in Life Sciences, Data/Analytics, Epidemiology, Public Health, or related field
Master's degree (MPH, MBA, Biostatistics, or Data Science)

Tools

Claude Code
Databricks
AWS

Job description

Bristol Myers Squibb is seeking a Senior Manager, Real-World Data Strategy to drive end-to-end RWD initiatives and AI-enabled data solutions. You will lead data product development, governance, and partnerships across R&D, HEOR, and analytics to accelerate insights that improve patient outcomes.

The role requires 4–5 years in data/analytics with hands-on experience in RWD sources and strong cross-functional collaboration.

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