IR
Scientist - Quantitative Pharmacology and Machine Learning
Integrated Resources, Inc
🇺🇸 United States
On-site
6 days ago
- Machine Learning
- SAS
- Python
- Git
- scikit-learn
- PyTorch
- TensorFlow
- AI
6 days ago
Location: Cambridge, MA
Duration: 6 Months+ Possible Extension
Pay Range: $55-$60/hr
Shift Schedule- 1st Mon-Fri- 9-5pm EST.
Manager Notes:
- Scientist - Quantitative Pharmacology and Machine Learning 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.
Description:
- 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.
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.
Scientist - Quantitative Pharmacology and Machine Learning · Integrated Resources, Inc