Develop and deploy ML/AI models to support safety signal detection, dose selection, PK/PD modeling, toxicology insights, and translational interpretation.
Implement representation‑learning, predictive modeling, and multivariate analytics for datasets spanning in vivo studies, in vitro assays, exposure‑response data, and pathology information.
Partner with scientific SMEs to design modeling strategies aligned with PSTS decision points.
Apply model governance, versioning, and validation standards consistent with R&D AI practices.
Build and maintain scalable data pipelines that integrate PSTS‑relevant data sources (e.g., toxicology studies, PK/PD datasets, biomarker readouts, animal study repositories).
Transform raw experimental outputs into standardized, analysis‑ready, AI‑ready datasets using Python, R, and cloud‑native services.
Contribute to harmonized scientific data models in collaboration with data engineering and ontology teams.
Work directly with toxicology, DMPK, and safety stakeholders to interpret scientific context and translate study designs into computational requirements.
Apply understanding of mechanism‑based toxicology, exposure‑response concepts, and in vivo study structures to guide data transformations and modeling strategies.
Enhance cross‑study comparability via standardized terminologies, metadata practices, and quality checks.
Collaborate with PSTS functional experts, R&D Data Science teams, and platform architects to ensure high-quality, scalable data solutions.

Requirements

Advanced degree (MS or PhD) in Data Science, Computational Biology, Toxicology, Pharmacology, Biomedical Engineering, Computer Science , or related field.
3+ years of experience applying machine learning and/or data engineering to scientific or biomedical datasets.
Proficiency with Python and/or R , SQL, and modern data engineering tooling (cloud computing, workflow orchestration, version control).
Experience with ML model development, evaluation, and deployment pipelines.
Experience working with biological, toxicology, PK/PD, or in vivo datasets.

Benefits

Vacation –120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
Holiday pay, including Floating Holidays –13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave – 80 hours in a 52-week rolling period
Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdata engineeringpredictive modelingmultivariate analyticsmodel governanceversioningvalidation standardsdata transformationdata pipelinesstandardized datasets

Soft Skills

collaborationcommunicationproblem-solvinginterpersonal skillsorganizational skills

Certifications

MS in Data SciencePhD in Data ScienceMS in Computational BiologyPhD in Computational BiologyMS in ToxicologyPhD in ToxicologyMS in PharmacologyPhD in PharmacologyMS in Biomedical EngineeringPhD in Biomedical Engineering