Data Science Leader
The ideal candidate brings a rare blend of hands-on clinical operations knowledge, advanced analytics expertise, and leadership capability, with a proven ability to translate complex data into actionable insights and scalable solutions.
Responsibilities
- Act as a trusted thought partner to the Clinical Operations, Study Management, Data Management, Biostatistics, Medical, and IT stakeholders
- Identify, frame, and prioritize business problems where data science and technology can deliver measurable value
- Translate clinical operations challenges into analytically tractable problems and solution roadmaps
- Influence decision-making at senior leadership levels using data-driven insights
- Lead development and deployment of advanced analytics solutions across the clinical trial lifecycle
- Apply predictive modeling, machine learning, optimization, and statistical techniques to real-world clinical operations problems
- Drive adoption of data-driven and AI-enabled approaches within clinical operations teams
- Define data strategies that integrate clinical trial data, operational data, real-world data, and external datasets
- Partner with data engineering and platform teams to ensure scalable, compliant, and fit-for-purpose data infrastructure
- Ensure analytics solutions align with regulatory expectations (e.g., GxP, FDA, EMA) and data privacy requirements
- Evaluate and guide the use of emerging technologies (AI/ML, automation, digital platforms) in clinical operations
Requirements
- 15-20 years of relevant professional experience, with hands-on background in pharmaceutical clinical operations (e.g., Clinical Operations, Study Management, Trial Oversight, or related functions)
- Understanding of the end-to-end clinical trial lifecycle and operational pain points
- Demonstrated experience working within regulated environments (GxP, clinical compliance)
- Advanced degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Life Sciences, or related field
- Strong foundation in statistical modeling, machine learning, and advanced analytics
- Familiarity with common data science tools and programming languages (e.g., Python, R, SQL)
- Exceptional communication skills with the capability to explain complex analytical concepts to non-technical stakeholders
- Proven track record of influencing senior leaders and driving organizational change through data
