Sr. Director, Real-world Data Strategy

Role Summary

The Senior Director, Real-World Data Strategy leads the delivery of BMS's global development and translational medicine RWD strategy and research platforms. This role oversees a global team of data strategists and scientists, directs the development of RWD assets and partnerships, and connects R&D and commercial priorities with emerging data opportunities. Deep expertise in clinical and genomics real-world data, the RWD compliance landscape, global RWD opportunities, and applying AI innovation is required.

Responsibilities

1. Develop and execute a global real-world data (RWD) strategy that aligns with BMS's research, translational medicine, and commercial goals.
2. Communicate strategic direction and decisions to internal and external stakeholders, ensuring organizational alignment.
3. Prioritize RWD investments based on business impact and strategic fit, tracking return on investment across functions.

Team & Partnership Management

1. Lead, grow, and empower a diverse global team of data strategists, scientists, and engineers.
2. Build and nurture collaborative relationships with internal stakeholders and external partners to expand RWD capabilities and foster innovation.
3. Identify opportunities for new partnerships and cultivate connections that drive data acquisition and solution development.

Data Acquisition, Quality & Compliance

1. Oversee acquisition, integration, and enablement of RWD assets to support research, development, and regulatory needs. Ensure fit-for-purpose data selection and avoid redundant purchases.
2. Implement robust data quality frameworks and standards, driving automation and harmonization across datasets and functions.
3. Ensure strict adherence to global compliance, privacy regulations, and ethical standards in all RWD activities.

Innovation & Advanced Analytics

1. Champion the application of AI, advanced analytics, and emerging technologies to unlock new insights and capabilities from RWD.
2. Deliver regulatory-grade RWD packages when needed (e.g., external control arms, label expansion).
3. Partner with cross-functional teams in biostatistics, epidemiology, and data science to ensure access to impactful data and support clinical and commercial use cases.

Enablement & Cross-Functional Integration

1. Facilitate centralized access to RWD for teams across Commercial, Medical, and R&D, enhancing usability and impact.
2. Provide training, guidance, and tools to democratize RWD use and empower teams to leverage data effectively.
3. Support key use cases such as medical studies, trial feasibility, external control arms, and post-marketing commitments.

Value Demonstration & Performance Measurement

1. Continuously measure and communicate the value of RWD investments using clear KPIs, dashboards, and case studies.
2. Monitor business impact, including improved trial timelines, patient targeting, and payer negotiations, ensuring effective utilization of assets.

Qualifications

• Educational Background: Master's degree in a research or quantitative field required; PhD preferred.
• Leadership and Communication: Strong consulting and influencing skills, proven capabilities in senior stakeholder engagement, matrix team leadership, and excellent writing and oral communication skills.
• Experience and Expertise: 10+ years in pharmaceutical health services, outcomes, or related research fields, with significant experience in clinico-genomic data and retrospective healthcare data sets; 7+ years of team leadership experience.
• RWD Strategy and Lifecycle: Expertise in leveraging Real-World Data (RWD) throughout the development lifecycle, including discovery, early/late development, and commercialization.
• Data Management and Governance: Proven ability to develop and manage integrated data sources using tokenization, with extensive experience in data ecosystem design, management, and governance.
• Global Collaboration and Compliance: Experience with US and ex-US data collaborators and licensors, deep understanding of global RWD landscape and privacy regulations (HIPAA, GDPR).
• Technical Proficiency: Strong knowledge of research applications (SAS, R, Python, SQL, Tableau), data platform technologies, and observational research methods.