Chemistry Data Science Intern - Digital CMC Workflows

Zoetis • Kalamazoo, MI

9d • Onsite

About The Position

Zoetis VMRD Process Chemistry is seeking a summer intern in Kalamazoo, Michigan, to help build and test a structured digital approach to managing process chemistry and analytical data. The intern will organize reaction, batch, purity, and impurity data from an active development program in a structured CMC data platform, build an impurity-fate case study, and benchmark the platform against the current workflow. The work will support an objective, data-backed recommendation on deploying digital CMC tools across the portfolio.

The role involves preparing and validating project data, mapping impurity formation and removal across a synthetic route, and comparing scientific tasks in the digital environment with the existing workflow. The intern will assess results using defined measures, document standards and data limitations, and present deployment recommendations to Process Chemistry, Analytical, and Tech & Digital stakeholders. This is a full-time summer internship.

Requirements

• Currently enrolled in a Bachelor’s, Master’s, or PhD program in Chemistry, Cheminformatics, Chemical Engineering, Data Science, Computational Chemistry, Analytical Chemistry, or a closely related field.
• Experience analyzing structured or semi-structured data using Python, R, SQL, Excel, or Power BI.
• Sufficient organic chemistry background to correctly interpret reaction schemes, HPLC/chromatographic data, and impurity profiles.
• Coursework in organic and analytical chemistry.
• Strong attention to data quality, traceability, and reproducibility, including documenting assumptions and flagging gaps rather than filling them in.
• Clear written and verbal technical communication skills, including the ability to present findings and defend conclusions to scientists and non-chemist stakeholders.

Nice To Haves

• Rising senior or graduate student.

Responsibilities

• Structure, clean, and validate reaction, batch, purity, and impurity data from an assigned process chemistry project, applying consistent compound and impurity naming conventions.
• Build an impurity-fate and data-retrieval case study in a structured CMC data environment, such as Luminata or an equivalent platform, mapping impurity formation, carry-through, and purge across the synthetic route.
• Design and execute a benchmark comparing defined scientific tasks in the digital environment with the current workflow.
• Measure time to correct answer, accuracy, traceability, data completeness, and the number of systems consulted.
• Analyze benchmark results and create a concise KPI scorecard identifying where structured data delivers measurable gains and where it does not.
• Document data standards, assumptions, and gaps.
• Deliver a final presentation with recommendations for broader deployment to Process Chemistry, Analytical, and Tech & Digital stakeholders.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: No Education Listed