Senior Director, Data Science Innovation Lead

Role Summary

Senior Director, Data Science Innovation Lead based in Waltham, MA, will pioneer transformative solutions in real-world evidence generation within the Real-World Data, Measurement, and Analytics (RWDMA) organization, supporting the entire drug development life cycle from early development to late-phase clinical trials and post-approval market access and reimbursement. The role will leverage advancements in data sciences such as multimodal AI, generative AI, knowledge graphs, causal AI, and agentic AI to develop and optimize statistical methodologies, support AI-driven automation tools, and deploy intelligent systems for efficient data processing while ensuring regulatory compliance.

Responsibilities

• Data Science Strategy & Leadership
  • Align RWDMA Data Science initiatives with RWD goals, regulatory requirements (FDA, EMA), and payer expectations to ensure strategic impact and compliance, particularly in RWD analytics.
  • Lead RWDMA Data Science in a matrix organization, collaborating with biostatisticians, clinical and subject matter experts, and regulatory specialists to lead innovative RWE applications and embed Data Science into RWD workflows.
• Innovative Applications of Data Science in RWE Generation
  • Design customized Data Science models for RWD analytic applications, including Comparative Effectiveness, Precision Medicine, Predictive Modelling, and Evidence Synthesis (e.g., meta-analysis, indirect treatment comparisons, network meta-analysis).
• Automation & Process Optimization
  • Automate coding (clinical coding and patient identification) and QC processes using AI-driven anomaly detection to ensure validity of statistical programs and data integrity.
  • Develop NLP tools to automate creation, review, and validation of analytic plans and protocols, ensuring regulatory and payer compliance.
  • Build AI systems to streamline administrative tasks and enhance operational efficiency across drug development phases.
• Data Strategy
  • Assess data gaps in RWD in alignment with DDF and D3 initiatives and inform data strategy with potential Data Science applications.
  • Collaborate with RWDSP, DDF, and data tech teams to optimize RWD storage, management, and access control for analytical workflows.
  • Provide technical leadership on the use of synthetic data in RWD and drug development.
• Collaboration & Thought Leadership
  • Mentor team members in advanced Data Science methodologies to foster innovation and technical excellence.
  • Lead methodological innovation and development in RWD Data Science and support mentoring and professional growth of junior staff.
  • Develop external engagement with academic partners and key opinion leaders (KOLs) to advance collaborative research in RWD Data Science.
  • Present analyses and insights at conferences, in publications, and in stakeholder meetings to demonstrate the value of RWD Data Science contributions.

Qualifications

• Education and experience
  • PhD in Data Science, Biostatistics, Computer Science, or a related field.
  • 15+ years in healthcare and life sciences, with significant exposure to pharmaceutical and/or medical device industries.
  • 10+ years in clinical development or RWE generation within regulated environments, including hands-on leadership of Data Science projects.
  • Demonstrated success in deploying DataOps, ModelOps, or MLOps pipelines in cloud platforms (e.g., Azure, AWS).
• Technical Skills
  • Expertise in statistical modelling and AI/ML techniques (e.g., CNNs, RNNs, Transformers).
  • Proficiency in generative AI (LLMs, RAG, GANs, VAEs, diffusion models) and tools (LangChain, LlamaIndex, CrewAI).
  • Strong programming skills in Python, R, TensorFlow, PyTorch; experience with cloud tools (Azure ML, AWS SageMaker), Docker, and GitHub.
  • Familiarity with multi-domain real-world data (clinical records, imaging, genomics, wearables, unstructured text).
• Achievements
  • Proven track record of innovation in Data Science applications for healthcare, evidenced by publications, patents, or industry recognition.
  • Experience navigating ethical, privacy, and regulatory challenges in AI-driven healthcare solutions.