Associate Director, Data Science

Novartis is seeking an experienced Data Science leader to advance data-driven drug discovery and development by integrating advanced analytics, machine learning, and mechanistic modelling approaches. The role will partner with Pharmacokinetic Sciences (PKS) Modeling & Simulation (M&S), Translational Medicine, and multidisciplinary project teams to transform large-scale experimental datasets into actionable insights.

What You Will Do

Key responsibilities include shaping and advancing AI-driven MIDD, designing and implementing hybrid modelling pipelines, translating model-derived biomarkers and mechanistic states into clinically relevant predictions, and driving scientifically grounded AI approaches.

Why It Might Be a Fit

The ideal candidate will have a strong understanding of ADME, PK/PD, and/or translational modelling concepts, proficiency in Python and/or R, and experience with machine learning libraries such as scikit-learn, PyTorch, or Keras.

Requirements

• Advanced degree in life sciences or quantitative discipline
• PhD with 5+ years or MSc with 8+ years of relevant experience in drug discovery or development
• Strong expertise in machine learning, statistics, and data science methods
• Demonstrated experience applying reproducible data science approaches to drug discovery or development
• Experience combining mechanistic modelling and data-driven approaches is strongly preferred
• Strong understanding of ADME, PK/PD, and/or translational modelling concepts
• Proficiency in Python and/or R, including software development best practices
• Experience with machine learning libraries such as scikit-learn, PyTorch, or Keras
• Strong data visualization and exploratory data analysis skills
• Ability to translate complex analytical concepts into clear, actionable insights
• Strong collaboration and communication skills across multidisciplinary teams
• Fluency in English (oral and written)

Benefits

• Comprehensive benefits package
• 401(k) with company contribution and match
• Performance-based cash incentive
• Annual equity awards
• Generous time off package
• Vacation
• Personal days
• Holidays
• Other leaves