ToxStrategies, Inc., is seeking a data scientist/bioinformatics scientist with experience analyzing and integrating chemical and biological data for purposes of predicting human exposures and assessing safety of chemicals. The position involves using mathematical modeling, machine learning, statistics, and data mining to characterize and better understand human exposures and associated health risks. The successful candidate should be proficient in programming languages (e.g., R, Python, Java, JavaScipt), as well as have a working knowledge of relational databases (e.g., MySQL, Postgres). In addition, the candidate should have a working knowledge of statistical approaches for evaluation of data, including the application of Bayesian methods and machine learning. Mastery of data presentation and visualization is essential. Familiarity with complex exposure models (e.g., SHEDs-HT, ExpoCast, SEEM3, etc.), high-throughput toxicity screening assays and data platforms, high-throughput toxicokinetics, “httk” R package, reverse TK, IVIVE, pharmacokinetic modeling, and CDC NHANEs data is considered a plus.