Director, Data Science Hybrid

Job Description

The Director Data Science (R-track) provides strategic leadership and governance for analytics and data enablement across multiple therapeutic areas. This individual defines and oversees the implementation of enterprise-wide data and analytics strategies ensuring high-quality automation methodological consistency and alignment with clinical and digital health objectives. The Director Data Science establishes governance frameworks drive cross-functional collaboration and advance innovation in analytical methodologies tools and automation.

Responsibilities

Data analysis insights and visualization

• Lead the development and execution of therapeutic-area data enablement and analytics strategies aligned with organizational goals.
• Guide the creation of analytics KPIs (Key Performance Indicators) 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.

Technical delivery automation ML/AI enablement

• 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.

Enterprise Leadership Skills

• Business Savviness Anticipates business and regulatory issues and shapes strategy accordingly; connects technical expertise to organizational and industry context to make strategic recommendations
• Influence Leads large teams / projects helps shape departmental strategy influences leaders peers and cross-functional partners to align on decisions and strategic direction
• Change Catalyst Drives improvements (e.g. organizational and cultural changes) with broader impact; demonstrates adaptability and ability to collaborate with others to make change successful; helps others overcome resistance to change

Qualifications & experience

• Bachelors 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 for job description including:
• 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.

OR

• Advanced Degree (Masters or Doctorate) in Computer Science Statistics Pharmacy Nursing Biological Sciences or health care related discipline with a minimum of 8 years of experience in relevant field for job description including:
• 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.

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The successful candidate will be eligible for annual bonus and long-term incentive if applicable.

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