Senior Manager, Real World Data Strategy

Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.

Job Description: Senior Manager, Real-World Data Strategy

Description

The Real-World Data (RWD) Strategy team stewards real-world data assets end-to-end, from strategic acquisition and governance to scalable data product development and AI-ready foundations, to democratize access, accelerate innovation, and improve patient outcomes.

The Senior Manager is a dynamic, cross-functional role spanning data landscaping, external partnerships, customer success, data product strategy, and governance. This individual translates strategic priorities into structured execution plans within a matrixed, collaborative environment, championing an AI-native mindset throughout.

Key Responsibilities

Strategy Execution & Delivery

• Lead end-to-end RWD initiative execution, from scoping through stakeholder sign-off, with clear milestones, owners, and risk mitigation strategies
• Track interdependent workstreams, proactively surface blockers, and escalate with solutions

AI Innovation & Technology Enablement

• Act as the team's AI driver: identify, pilot, and embed AI/ML tools and automation into RWD workflows, data pipelines, and analytical processes
• Ensure RWD assets are structured and documented for AI/ML downstream consumption in partnership with engineering and data science teams

Data Landscaping, Products & Partnerships

• Evaluate and onboard external RWD sources (claims, EHR, registries, labs, PROs); manage vendor assessments, acquisition workflows, and data access governance

• Design scalable data products across Research, Development & HEOR; engage internal customers to drive adoption and usability

Value, Impact & Governance

• Define and track KPIs demonstrating the impact of RWD investments and data products
• Uphold data quality, governance standards, metadata practices, and compliance requirements; contribute to lineage documentation and enablement resources

Position Requirements

Education

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

Experience

• 4–5 years in data, analytics, real-world evidence, consulting, or a related field
• Hands-on experience with RWD sources (claims, EHR, molecular, biomarker, imaging), including knowledge of their structure, limitations, and appropriate use cases
• Track record delivering data products or analytics solutions: scoping, timeline management, and fit-for-purpose outputs (e.g., analytical datasets, data platforms, self-service tools)
• Experience in cross-functional, matrixed environments across technology, analytics, and business stakeholders
• Demonstrated hands-on proficiency with AI-native tools, specifically Claude Code and collaborative AI coding environments, applied to data workflows, scripting, or pipeline development; a pre-interview hands-on project may be required

Required Skills

Technical

• SQL proficiency; working knowledge of R or Python for data manipulation, QC, or analytical workflows
• Familiarity with data pipelines and cloud environments (e.g., Databricks, AWS)
• Proficiency with Claude Code and collaborative AI tools to accelerate querying, QC automation, and documentation; ability to integrate AI into structured workflows via prompt engineering and AI-assisted analysis
• Understanding of data quality frameworks and governance practices

Professional & Leadership

• Strong execution and delivery management: organized, detail-oriented, a