Leading and providing strategic oversight for the Analytical Safety Strategy across GMS, ensuring alignment with organizational goals and regulatory expectations.
Developing, testing, validating, and implementing quantitative approaches including safety signal detection, signal evaluation, GenAI and machine learning methods for safety assessments, trend and pattern recognition, and process-optimization analytics.
Designing and overseeing rapid data retrieval systems, dashboards, and analytic workflows to enable time-critical decision making for senior management during urgent/emergency scenarios.
Building, coaching, and managing a multidisciplinary team responsible for setting function-level analytical strategy, creating reproducible methods and tools, and delivering high-quality analytics and reports.
Evaluating and operationalizing novel analytic tools and computer-assisted methodologies for internal safety data and relevant external data sources.
Leading cross-functional collaborations with IT, Pharmacoepidemiology, Clinical Safety, Preclinical Safety, and other internal groups; representing the organization in cross-industry safety analytics initiatives.
Serving as a thought leader in safety analytics through internal education, external presentations, and peer-reviewed publications.

PhD in Biomedical Science, Biostatistics, Computational Analysis or a related field, plus 10+ years of industry experience in drug safety analytics or closely related areas at a global pharmaceutical company or large CRO.
Demonstrated in-depth understanding of computational signal detection algorithms and statistical methods used in pharmacovigilance, including disproportionality methods.
Knowledge of Large Language Models and experience with their application in drug safety.
Strong understanding of quality measurement frameworks, specifically in the area of GenAI.
Proven leadership experience managing and developing teams of statisticians, data scientists, and programmers; strong decision-making and stakeholder-management skills.
Hands-on experience with at least one of the following analytical/visualization platforms or languages: R / RShiny, Python, PL/SQL, Qlik scripting.
Working knowledge of scientific programming and statistical tools for aggregate data analysis, trend analysis and pattern recognition.

Requires the ability to work on-site a minimum of three days per week, with the option for up to two remote days, in alignment with our flexible work policy.

Senior Director – Head of GMS Safety Analytics

Key skills