Director, Data Science - Hybrid

Responsibilities

• Lead the development and execution of therapeutic-area data enablement and analytics strategies aligned with organizational goals.
• Guide the creation of analytics KPIs and dashboards to monitor data performance, quality, and operational efficiency across therapeutic areas.
• Serve as a key advisor to executive leadership, governance boards, and cross-functional leaders by translating analytical insights into strategic business decisions.
• Maintain accountability for the design, performance, and integrity of automated data and analytics pipelines, ensuring scalability and compliance with regulatory standards.
• Oversee analytics governance to ensure consistent application of standards, metrics, and quality controls across programs and platforms.
• Drive adoption of emerging technologies (e.g., AI/ML, advanced data visualization, predictive analytics) and promote continuous improvement in analytical efficiency and value generation.
• Define and enforce best practices for dataset design, feature engineering, and analytical evaluation to ensure comparability and reproducibility across studies.
• Lead and mentor analytics team members, fostering an environment of innovation, accountability, and collaboration.
• Strengthen organizational analytics maturity through targeted capability development and knowledge-sharing initiatives.
• Partner with clinical, data management, and IT teams to ensure cohesive, interoperable analytics processes that drive meaningful business and scientific outcomes.
• Champion organizational change; drive adoption of new operating models and digital capabilities across global functions.

Technical Skills

• Expert knowledge of analytics governance frameworks, successful data strategy implementation, and cross-functional data integration techniques.
• Expert knowledge in advanced data analytics, automation, and AI/ML evaluation applied to clinical and digital health data.
• Expert experience in designing and overseeing automated analytics pipelines, data architectures, and metadata-driven workflows.
• Expert command of programming languages and analytics tools (e.g., Python, R, SQL) as well as data visualization and monitoring platforms (e.g., Power BI, Tableau, Spotfire).
• Expert knowledge of clinical and real-world data standards (e.g., CDISC, SDTM) and of regulatory compliance requirements (e.g., GxP, 21 CFR Part 11).
• Expert experience driving enterprise-scale data transformation initiatives and enabling scalable, technology-driven analytics ecosystems.

Non-Technical Skills

• Ability to distill complex issues into decision-ready narratives; frames options, risks, and recommendations to influence senior decisions.
• Strong proficiency in driving adoption of standardized methods/ways of working; mobilizes cross-functional champions and measures uptake.
• Capable of aligning senior stakeholders on objectives, interfaces, and responsibilities, while ensuring clean handoffs and conflict resolution.
• Coordinates decisions across regions/time zones; uses asynchronous mechanisms to maintain momentum.
• Engages vendor forums; represents team professionally and credibly under pressure; maintains resilience and composure.
• Resilient and adaptable, with a balance of strategic vision and operational execution.
• Ability to integrate business, operational, and people dimensions into decision-making.

Qualifications & Experience

Bachelor's Degree in Computer Science, Statistics, Pharmacy, Nursing, Biological Sciences, or health care related discipline with a minimum of 10 years of experience in relevant field, OR Advanced Degree (Masters or Doctorate) in a relevant discipline with a minimum of 8 years of experience.

• Demonstrated aptitude of working with large datasets to transform into actionable insights, deep subject matter expertise in relevant discipline.
• People management skills.
• Programming and/or analysis experience may include SQL, Python, R, Databricks and the like.
• Expert knowledge of statistics, data visualization, organizational skills, time management, and database concepts.