Job Description

We have an exciting opportunity for a Lead Exposure Data Scientist at UL Research Institutes, based in our Morrisville, NC office.

The Lead Exposure Data Scientist will be responsible for assisting in the development and maintenance of the data analysis infrastructure to support Chemical Insights’ mission of advancing human and environmental health. This role focuses on developing data analysis pipelines, ensuring efficient data exchange and interoperability across diverse platforms and scientific disciplines, and applying advanced machine learning/AI methods and statistical frameworks to identify and quantify trends or patterns in complex, large scale datasets. The Lead Exposure 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.

What you’ll learn and achieve:

As the Lead Exposure Data Scientist, you will play a key role in the rapid growth of ULas you:

• Design and implement cutting-edge data science methods for chemical exposure.
• Work as part of a team to extract, curate, and harmonize structured and unstructured chemical exposure, product ingredient, biomonitoring, and environmental contamination data.
• Develop and implement quality assurance plans for data curation projects.
• Design and implement artificial intelligence and machine learning solutions to automate data extraction, curation, and quality evaluation of structured and unstructured data.
• Develop and implement data mapping and extraction, transformation, and load (ETL) pipelines for efficient exchange of data between established chemical 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 provide solutions for linking cross-disciplinary data, computational modeling, and interpreting experimental results.
• Work closely with software and database engineers to provide high-quality chemical exposure data for on-line 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 up to date with the latest research and advancements 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.
• Perform other duties as assigned.

What you’ll experience working at UL Research Institutes: We have pursued our mission of working for a safer, more secure, and sustainable world for nearly 130 years, embedding conscientious stewardship into everything we do.

• People: Our people make us special. You’ll work with a diverse team of experts respected for their independence and transparency and build a network, because our approach is collaborative. We collaborate across disciplines, organizations, and geographies to build the global scientific response that today’s global challenges require.
• Interesting work: Every day is different for us here. We see what’s on the horizon and use our expertise to build the foundations of a safer future. You’ll have the opportunity to push the boundaries of human understanding as part of a team working to advance the public good.
• Grow and achieve: We learn, work, and grow together through targeted development, reward, and recognition programs.
• Values. Four core values guide our work: collaboration, respect, integrity, and beneficence. By living our values, we inspire the trust essential to fulfilling our mission and foster the partnerships that enable us to pursue a beneficent future in which we all can thrive.
• Total Rewards: All employees at UL Research Institutes are eligible for bonus compensation. We offer comprehensive medical, dental, vision, and life insurance plans and a generous 401k matching structure of up to 5% of eligible pay. Moreover, we invest an additional 4% into your retirement saving fund after your first year of continuous employment. Depending on your role, you may be able to discuss flexible working arrangements with your manager. We also provide employees with paid time off, including vacation, holiday, sick, and volunteer days.

What makes you a great fit:

While no one candidate will embody every quality, the successful candidate will bring many of the following professional competencies and personal attributes:

• Proficiency in programming and statistical languages (e.g. 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 versioning best practices, i.e. GitHub, Code Commit.

Professional education and experience requirements for the role include:

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

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