Senior Manager, Real-World Data Strategy | AI-Driven

Bristol-Myers Squibb; United States; On-site; USD 139,000 - 169,000; Full time

Benefits offered by this job

Health Coverage

Wellbeing Programs

401(k) plan

Paid time off

Job summary

Bristol Myers Squibb in the United States seeks a Senior Manager, Real World Data Strategy to lead end-to-end RWD initiatives, drive AI-enabled data product strategy, and collaborate across technology, analytics and business partners.

You will scope projects, manage timelines, onboard external data sources, and measure KPI impact while upholding governance and data quality standards in a fast-paced, matrixed environment.

Qualifications

• Bachelor's degree in Life Sciences, Data/Analytics, Epidemiology, Public Health, or related field.
• Master's degree (MPH, MBA, Biostatistics, or Data Science) preferred.
• 4–5 years in data, analytics, real-world evidence, consulting, or related field.
• Hands-on experience with RWD sources (claims, EHR, registries, labs, PROs).

Responsibilities

• Lead end-to-end RWD initiative execution with milestones and risk mitigation.
• Identify, pilot, and embed AI/ML tools into RWD workflows and data pipelines.
• Evaluate and onboard external RWD sources; manage vendor assessments and governance.
• Define and track KPIs to demonstrate RWD investments and data product impact.

Skills

SQL proficiency

R

Python

Claude Code

Databricks

AWS

Education

Bachelor's in Life Sciences, Data/Analytics, Epidemiology, Public Health, or related field

Master's degree (MPH, MBA, Biostatistics, or Data Science) preferred

Tools

Claude Code

Databricks

Collaborative AI tools

Job description

Bristol Myers Squibb in the United States seeks a Senior Manager, Real World Data Strategy to lead end-to-end RWD initiatives, drive AI-enabled data product strategy, and collaborate across technology, analytics and business partners.

You will scope projects, manage timelines, onboard external data sources, and measure KPI impact while upholding governance and data quality standards in a fast-paced, matrixed environment.