About this opportunity
Sanofi lists this Data Scientist (contract) opportunity in cambridge, Massachusetts. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Sanofi's contingent workforce program, FLEXT Direct, is seeking a Data Scientist for a 6-month contract supporting Sanofi's Quantitative Pharmacology (QP) group.
Position Overview
The Quantitative Pharmacology (QP) group is seeking a Data Science contractor to develop and enhance pharmacokinetics (PK)/pharmacodynamics (PD) modeling, data analysis, and decision-support tools for drug discovery and development.
The successful candidate will work closely with QP scientists to develop robust, validated, reproducible, and user-friendly computational solutions. This role combines Python programming, scientific data analysis, mathematical and statistical modeling, machine learning, and scientific software development.
Key Areas Of Work May Include
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
Qualifications
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
Preferred Qualifications
Familiarity with PK/PD modeling
Experience with dynamical systems, time-series, or longitudinal data
Experience working with molecular structures, compound descriptors, or experimental drug-development data
Familiarity with AI-enabled or agentic workflows for automating and orchestrating data analysis, model execution, scientific interpretation, and reporting
Experience in pharmaceutical, biotechnology, drug discovery, or related scientific research environments
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Worksite address
cambridge, MA, 02140, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.