Lead Exposure Data Scientist
Core
Developing data analysis pipelines and applying machine learning/AI to identify trends in large-scale chemical exposure datasets for human and environmental health risk assessment.
Role type
Lead Exposure Data Scientist
Builds
Data analysis infrastructure, ETL pipelines, and predictive models for chemical exposure assessment.
Domain
Environmental health, chemical safety, and toxicology
Deliverable
production ML models | dashboards & analysis
Required skills
Python, R, Java, SQL, Postgres, machine learning, statistical modeling, data curation, ETL pipeline development, relational and non-relational databases
Preferred skills
exposure science, chemistry, toxicokinetics, data visualization, GitHub version control
Responsibilities
Design and implement data science methods for chemical exposure; extract, curate, and harmonize chemical exposure and environmental contamination data; develop AI/ML solutions to automate data extraction and quality evaluation; build ETL pipelines for data exchange between chemical safety systems; develop statistical and ML models to predict chemical functional use and exposure pathways; collaborate with scientists to link cross-disciplinary data and interpret results.
Seniority
Lead, hands-on IC with mentorship
