Biostatistician with SAS Programming

Scientist – Quantitative Pharmacology and Machine Learning

Location: Cambridge, MA

Pay Rate: $ 59.14/hour

Schedule: Monday–Friday, 9:00 AM–5:00 PM

Hours: 40 hours/week

Contract: Full duration of assignment

Dress Code: Professional

Assessment: N/A

Position Overview

Our Quantitative Pharmacology (QP) group is seeking a Scientist – Quantitative Pharmacology and Machine Learning to support the development of innovative computational tools for drug discovery and development.

This role will focus on PK/PD modeling, data analysis, machine learning, scientific computing, and decision-support tools . The successful candidate will work closely with QP scientists to develop robust, validated, reproducible, and user-friendly computational solutions that support compound prioritization and early drug development decisions.

The position offers an opportunity to contribute to projects spanning multiple therapeutic areas and research platforms within a broader R&D organization.

Key Responsibilities

• Develop and enhance pharmacokinetic/pharmacodynamic (PK/PD) models and quantitative pharmacology tools.

• Build interactive scientific applications using Python and Shiny for Python or related frameworks.

• Develop automated analytical workflows to streamline scientific data analysis.

• Create model diagnostics, data visualizations, and decision-support tools.

• Perform scientific data analysis and develop mathematical and statistical models.

• Develop and evaluate machine learning models supporting compound prioritization and early drug development decisions.

• Integrate molecular structures, compound descriptors, experimental data, and other relevant datasets to predict pharmacokinetic and pharmacological properties of small molecules.

• Develop reproducible computational workflows for scientific analysis.

• Apply software development best practices, including version control, testing, documentation, and reproducibility.

• Collaborate closely with Quantitative Pharmacology scientists and cross-functional teams.

• Explore agentic AI-enabled workflows to automate and orchestrate data analysis, model execution, interpretation, and reporting.

• Support model validation and ensure computational tools are robust, reliable, and user-friendly.

• Communicate technical findings and collaborate effectively in a matrixed and global R&D environment.

Required 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 experience .

• Strong proficiency in Python .

• Experience developing interactive applications using Shiny for Python or related frameworks.

• Familiarity with software development practices, including:

• Git/version control

• Software testing

• Documentation

• Reproducible workflows

• Familiarity with machine learning model development, evaluation, and validation.

• Experience or familiarity with machine learning libraries/frameworks such as Scikit-learn, PyTorch, TensorFlow, or Keras .

• Strong collaboration and communication skills.

• Ability and willingness to learn new technologies and scientific approaches.

• Ability to work effectively in a matrixed and global environment .

• Must be able to work 40 hours per week, Monday–Friday, for the full duration of the contract .

• Must meet applicable U.S. work authorization requirements for the contractor position.

Preferred Qualifications

• Experience with scientific data analysis and visualization.

• Experience with mathematical and statistical modeling.

• Familiarity with PK/PD modeling .

• Knowledge of dynamical systems, time-series analysis, or longitudinal data.

• Familiarity with agentic AI and AI-enabled workflows .

• Experience automating and orchestrating data analysis, model execution, scientific interpretation, or reporting.

• Interest in applying machine learning and computational methods to drug discovery and development.

Ideal Candidate

The ideal candidate is a technically strong and collaborative data scientist or computational scientist who enjoys applying Python, machine learning, mathematical modeling, and software development to real-world scientific problems. The candidate should be comfortable working with scientists, learning new methodologies, and developing reproducible tools that improve scientific decision-making.

Work Schedule

Monday–Friday | 9:00 AM–5:00 PM

40 hours per week

Candidates must be available to work the full duration of the contract.

Pay Details: $59.14 per hour

Benefit offerings available for our associates include medical, dental, vision, life insurance, short-term disability, additional voluntary benefits, EAP program, commuter benefits and a 401K plan. Our benefit offerings provide employees the flexibility to choose the type of coverage that meets their individual needs. In addition, our associates may be eligible for paid leave including Paid Sick Leave or any other paid leave required by Federal, State, or local law, as well as Holiday pay where applicable.

Equal Opportunity Employer/Veterans/Disabled

Military connected talent encouraged to apply

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The Company will consider qualified applicants with arrest and conviction records in accordance with federal, state, and local laws and/or security clearance requirements, including, as applicable:

• The California Fair Chance Act

• Los Angeles City Fair Chance Ordinance

• Los Angeles County Fair Chance Ordinance for Employers

• San Francisco Fair Chance Ordinance

Massachusetts Candidates Only: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.