Scientist Quantitative Pharmacology & Machine Learning

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 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.

Immediate need for a talented Scientist – Quantitative Pharmacology & Machine Learning. This is a 06 Months Contract opportunity with long-term potential and is located in Cambridge, MA (Onsite). Please review the job description below and contact me ASAP if you are interested.

Job ID:26-30142

Pay Range: $50 - $55/hour.  Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location).
 
Key Responsibilities:

• The Quantitative Pharmacology (QP) group at Client 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.

Key Requirements and Technology Experience:

• Skills- Programming and scientific/data analysis.; Machine Learning; experience with statistical modeling, predictive modeling, scientific computing, or ideally PK/PD/time-series data
• 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.

Our client is a leading Pharmaceutical Industry and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration.
 
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