Senior Manager, Data Strategy

At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits.

This is work that transforms the lives of patients, and the careers of those who do it.

Description

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

• 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

• 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

• 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

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

• 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

• 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

• Strong execution and delivery management: organized, detail-oriented, able to juggle competing priorities
• Hands‑on AI capability is a core, non‑negotiable requirement: candidates must demonstrate active, daily use of AI tools (including Claude Code) with tangible examples of impact on workflows, automation, and team delivery; this is an expected competency aligned with BMS's enterprise‑wide AI-native commitment
• Clear communicator across technical and…