UL Research Institutes is looking for a Chemistry Data Scientist to support the Chemical Insights Research Institute (CIRI) mission of advancing human and environmental health by developing data analysis infrastructure, ensuring data interoperability, and applying machine learning/AI to complex datasets for chemical risk assessment and public health guidance.
Requirements
- Proficiency in programming and statistical languages (e.g. Python, R).
- Knowledge of machine learning, statistical modeling, and data visualization tools.
- Working knowledge of chemistry, toxicology, toxicokinetics, and exposure science.
- Understanding of relational database systems.
- Skilled in versioning best practices, i.e. GitHub, Gitlab, Code Commit.
- Solid technical knowledge and experience working with R and Python programming language, relational (SQL and Postgres) databases.
- Prior experience working to develop data extraction, processing, and curation workflows for mass spectra data from diverse formats.
Responsibilities
- Design and implement cutting-edge data science methods for chemical safety.
- Work as part of a team to extract, curate, and harmonize structured and unstructured chemistry data including analytical methods, experimental spectra, and physio-chemical properties.
- 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 data systems (e.g., DSSTox, AMOS).
- Develop and maintain data analysis pipelines for analytical chemistry spectra and data and physicochemical properties.
- Assist in the implementation and maintenance of laboratory information management system (LIMS) and electronic laboratory notebook for CIRI.
- Collaborate with chemists, toxicologists, exposure scientists, and toxicokinetic scientists to provide solutions for linking cross-disciplinary data, computational modeling, and interpreting experimental results.
Other
- Proven ability to participate in multidisciplinary teams on complex projects in a research setting.
- 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.
- Ability to communicate with technical and non-technical internal and external stakeholders.
- Bachelor’s degree in Chemistry, Statistics, Data Science or a related field and a minimum of 4 years of relevant experience in data science,
