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Jobs · OTHR · Massachusetts

Scientist - Quantitative Pharmacology and Machine Learning

eTeam · Cambridge, MA · 3 wk ago
On-siteOTHRContract

About the role

The client's Quantitative Pharmacology (QP) group seeks 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, which 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.

Responsibilities

  • Support the development and enhancement of quantitative pharmacology tools, including PK/PD models.
  • Develop interactive applications using Python and Shiny for Python.
  • Create automated analytical workflows, model diagnostics, and visualization.
  • Implement agentic AI‑enabled workflows to streamline scientific analysis and decision making.
  • Perform data analysis and develop mathematical and machine learning models for compound prioritization and early drug development decisions.
  • Integrate molecular structures, compound descriptors, experimental data, and other relevant information to predict pharmacokinetic and pharmacological properties of small molecules.
  • 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.

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 relevant experience.
  • Strong collaboration skills and openness to learning.
  • 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. requirements for the contractor position.

Skills

  • 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.
  • 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 agentic and AI‑enabled workflows for automating and orchestrating data analysis, model execution, scientific interpretation, and reporting is a plus.

Schedule

Location: Cambridge, MA. Duration: 6 months. Work schedule: Monday‑Friday, 9 AM‑5 PM EST (40 hours/week) for the full contract term.

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