Scientist - Quantitative Pharmacology and Machine Learning

Title: Scientist - Quantitative Pharmacology and Machine Learning
Location: Cambridge, MA 02141
Duration: 6 months
HM Notes:
Bachelor's degree or higher in Computer Science, Engineering, Data Science, Applied Mathematics, or a related quantitative field, with a strong background in software development and scientific computing. 1-3 years of experience. Strong collaboration skills and open to learning. Proficiency in Python with some experience developing interactive applications using Shiny for Python or related frameworks. Familiarity with software development practices including Git, testing, documentation, and reproducible workflows. Familiarity with machine learning model development, evaluation, and validation, using libraries and frameworks such as Scikit-learn, PyTorch, TensorFlow, or Keras.

Summary:
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 support the development and enhancement of quantitative pharmacology tools, including PK/PD models, interactive applications using Python and Shiny for Python, automated analytical workflows, model diagnostics and visualization, and agentic AI-enabled workflows to streamline scientific analysis and decision making.

The role will also involve data analysis and the development of mathematical and machine learning models to support compound prioritization and early drug development decisions. This may include integrating molecular structures, compound descriptors, experimental data, and other relevant information to predict pharmacokinetic and pharmacological properties of small molecules. The successful candidate will work closely with QP scientists to develop robust, validated, reproducible, and user-friendly computational solutions including exploring agentic approaches to automate and orchestrate data analysis, model execution, interpretation, and reporting.

The QP group supports multiple therapeutic areas and research platforms within the broader R&D organization.

Preferred Requirements:
Bachelor's degree or higher in Computer Science, Engineering, Data Science, Applied Mathematics, or a related quantitative field, with a strong background in software development and scientific computing.
1-3 years of experience.
Proficiency in Python, with 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 PK/PD modeling, dynamical systems, time-series, or longitudinal data is a plus.
Familiarity with machine learning model development, evaluation, and validation, using libraries and frameworks such as Scikit-learn, PyTorch, TensorFlow, or Keras.
Familiarity with agentic and AI-enabled workflows for automating and orchestrating data analysis, model execution, scientific interpretation, and reporting is a plus.
Ability to work effectively in a matrixed and global environment.
Must be able to work 40 hours/week, Monday-Friday, for the full duration of the contract.
Must meet applicable U.S. work authorization requirements for the contractor position.