Principal Exposure Data Scientist - Chemical Insights Research Institute

Job Overview

Principal Exposure Data Scientist – Work in the Chemical Insights Research Institute (CIRI) at UL Research Institutes, Morrisville, NC. This role develops and maintains data analysis infrastructure to support CIRI’s mission of advancing human and environmental health, leveraging advanced machine learning and statistical methods to identify and quantify exposure trends within large, complex datasets.

• Design, implement, and maintain cutting‑edge data science methods for chemical exposure.
• Extract, curate, and harmonize structured and unstructured chemical exposure, product ingredient, biomonitoring, and environmental contamination data.
• Develop and execute quality assurance plans for data curation projects.
• Create AI and machine learning solutions that automate data extraction, curation, and quality evaluation.
• Build ETL pipelines for efficient data exchange between safety and exposure data systems (e.g., IUCLID, MMDB, CPDat).
• Develop statistical and machine learning models to predict chemical functional use and exposure pathways.
• Collaborate with exposure scientists, toxicologists, analytical chemists, and toxicokinetic scientists to link cross‑disciplinary data, perform computational modeling, and interpret experimental results.
• Partner with software and database engineers to deliver high‑quality chemical exposure data for online decision‑support tools.
• Communicate complex technical concepts, methodologies, and results to senior management, partners, and stakeholders.
• Stay current on advances in data science, machine learning, and AI; contribute to new methodology development.
• Present research findings at scientific conferences, stakeholder meetings, and technical forums.
• Co‑author peer‑reviewed publications and technical reports.
• Assist in writing research proposals and securing internal and external funding.
• Provide technical support and troubleshoot data‑related issues.
• Perform other duties as assigned.

• Proficiency in programming and statistical languages (Python, Java, R).
• Knowledge of machine learning, statistical modeling, and data visualization tools.
• Working knowledge of exposure science, chemistry, and toxicokinetics.
• Understanding of relational and non‑relational database systems.
• Proven ability to lead multidisciplinary teams on complex research projects.
• Excellent problem‑solving and analytical capabilities, with the ability to adapt to new challenges and prioritize competing demands.
• Willingness to learn and research new concepts and technologies.
• Strong communication skills with technical and non‑technical stakeholders.
• Experience with version control best practices (Git Hub, Code Commit).
• Master’s degree in Environmental Health, Data Science, Chemistry, or Chemical Engineering plus 6+ years of relevant experience,
  * or*
• Doctoral degree in the same fields plus 4+ years of relevant experience.
• Solid technical knowledge and experience working with R, Java, or Python programming languages and relational databases (SQL, Postgres).
• Demonstrated experience developing data extraction and curation workflows for structured and unstructured chemical exposure data in a research environment.
• Prior experience developing quantitative structure‑property relationship models to predict chemical functional use and exposure pathways.

Salary Range: $ – $ (Annual).

Bonuses, comprehensive medical, dental, vision, and life insurance plans, and a generous 401(k) matching structure of up to 5% of eligible pay. UL contributes an additional 4% to retirement savings after the first year of continuous employment. Flexible work arrangements available. Paid time off includes vacation, holiday, sick, and volunteer days.

Morrisville, North Carolina (on‑site). The position may require occasional travel.