Data Scientist (contract)

Sanofi is seeking a Data Scientist contractor to support its Quantitative Pharmacology group. The role focuses on developing PK/PD models, scientific data analysis, machine learning models, and reproducible Python-based decision-support tools for drug discovery and development.

What you'll do:

• Developing and enhancing PK/PD models and quantitative pharmacology tools
• Performing scientific data analysis, visualization, and model diagnostics
• Developing interactive applications using Python and Shiny for Python
• Building automated and reproducible analytical workflows
• Developing mathematical and machine learning models to support compound prioritization and early drug development decisions
• Integrating molecular structures, compound descriptors, experimental data, and other relevant information to predict pharmacokinetic and pharmacological properties of small molecules
• Exploring AI-enabled and agentic workflows to automate and orchestrate data analysis, model execution, interpretation, and reporting
• Supporting computational solutions across multiple therapeutic areas and research platforms within Sanofi's broader R&D organization

What they're looking for:

• Bachelor's degree or higher in Computer Science, Engineering, Data Science, Applied Mathematics, or a related quantitative field
• Strong background in software development and scientific computing
• 1–3 years of relevant professional experience
• Proficiency in Python
• Some experience developing interactive applications using Shiny for Python or related frameworks
• Familiarity with software development practices, including Git, testing, documentation, and reproducible workflows
• Experience with scientific data analysis, visualization, and mathematical/statistical modeling
• Familiarity with machine learning model development, evaluation, and validation
• Experience with or familiarity with machine learning libraries/frameworks such as scikit-learn, PyTorch, TensorFlow, or Keras
• Ability to work effectively in a matrixed and global environment
• Familiarity with PK/PD modeling
• Experience with dynamical systems, time-series, or longitudinal data