Job Title: Data Scientist
Location: Thousand Oaks, California (On-Site)
Job Summary: We are partnering with a leading organization seeking a Data Scientist to support data-driven process development across chemistry-focused workflows. This role combines predictive modeling, cheminformatics, experiment design, and data pipeline development to help turn complex experimental data into practical, reusable insights.
Responsibilities:
- Develop regression and classification models to predict chemical reactivity and reaction outcomes using process parameters and molecular descriptors.
- Maintain molecular and physicochemical descriptor databases to support modeling and decision-making.
- Build active learning and Bayesian optimization workflows to guide experiment selection and iterative design-make-test-analyze cycles.
- Collaborate with process chemists, analytical scientists, automation scientists, and other subject matter experts to create modeling-ready datasets and translate results into actionable recommendations.
Required:
- Doctorate degree, or equivalent, in chemistry, chemical engineering, computer science, data science, cheminformatics, or a related field; or a Master’s degree, or equivalent, in one of these fields with 3 years of scientific experience; or a Bachelor’s degree, or equivalent, in one of these fields with 5 years of scientific experience.
- Demonstrated ability to work in cross-functional teams of chemists, engineers, and data scientists for data-driven chemical development.
- Strong knowledge of Python language (greater than 3.10) and mainstream data science and cheminformatics packages, including numpy, scipy, pandas, scikit-learn, and RDKit.
- Experience with applying Density Functional Theory (DFT) to molecular property and descriptor calculations.
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