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Lead Exposure Data Scientist at UL Research Institutes, based in our Morrisville, NC office. The role focuses on developing data analysis pipelines, ensuring efficient data exchange and interoperability across diverse platforms, and applying advanced machine learning/AI methods and statistical frameworks to identify and quantify trends in complex, large‑scale datasets. The Data Scientist works closely with Chemical Insights scientists and external collaborators to deliver high‑quality scientific data that informs chemical exposure assessment, risk assessment, regulatory decisions, and public health guidance.

• Assist in the development and maintenance of data analysis infrastructure to support Chemical Insights’ mission.
• Design and implement cutting‑edge data science methods for chemical exposure, including data extraction, curation, and harmonization of structured and unstructured chemical exposure, product ingredient, biomonitoring, and environmental contamination data.
• Develop and implement quality assurance plans for data curation projects.
• Create and maintain artificial intelligence and machine learning solutions to automate data extraction, curation, and quality evaluation.
• Develop data mapping and ETL pipelines for efficient exchange of data between chemical safety and exposure data systems (e.g., IUCLID, MMDB, CPDat).
• Build and validate 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, conduct computational modeling, and interpret experimental results.
• Work closely with software and database engineers to provide high‑quality chemical exposure data for online software applications and decision‑support tools.
• Effectively communicate complex technical concepts, methodologies, and results to diverse audiences, including senior management, amplification partners, and data stakeholders.
• Stay current with advances in data science, machine learning, and artificial intelligence, and contribute to the development of new methodologies and best practices.
• Present research findings at scientific conferences, stakeholder meetings, and technical forums.
• Serve as co‑author on peer‑reviewed publications and technical reports.
• Assist in writing research proposals and securing funding from internal and external sources.
• Provide technical support and troubleshooting for data‑related issues, and 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 participate in multidisciplinary teams on complex projects in a research setting.
• Demonstrated 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.
• Ability to communicate with technical and non‑technical internal stakeholders.
• Skilled in version control best practices (GitHub, Code Commit).

• Master’s Degree in Environmental Health, Data Science, Chemistry, or Chemical Engineering with at least 5 years of relevant experience; or
• Doctoral Degree in Environmental Health, Data Science, Chemistry, or Chemical Engineering with at least 3 years of relevant experience.
• Solid technical knowledge and experience with R, Java or Python.
• Experience working with relational databases (SQL, Postgres).
• Demonstrated experience developing data extraction and curation workflows for structured and unstructured chemical exposure data in a research environment.

Salary range: (provide range if available). The role offers bonus compensation, comprehensive medical, dental, vision, and life insurance plans, a generous 401(k) matching structure up to 5% of eligible pay, and a 4% additional retirement contribution after the first year of continuous employment. Employees also receive paid time off (vacation, holidays, sick, volunteer days) and can discuss flexible working arrangements with their manager. UL Research Institutes fosters a culture of collaboration, respect, integrity, and beneficence, providing professional growth through targeted development, reward, and recognition programs.