Some roles ask you to follow a process. This one asks you to shape it. At Zoetis, we're advancing the science of animal health-and we're looking for a scientist or engineer who can run bioreactors, think in models, and turn data into decisions. At the junction of upstream bioprocess development and modern analytics, you'll design studies with DoE, lead multivariate analysis, and build reproducible, interpretable models that drive process improvements and higher yields.
You'll partner across biology, engineering, and data science by listening well, learning quickly, and communicating clearly to move decisions forward faster. If you're ready to take ownership, change how we develop processes, and accelerate your career in a space where science meets purpose, we'd love to meet you.
Responsibilities
Design, run, and interpret mammalian cell culture experiments in shake flasks and bioreactors for monoclonal antibodies and proteins
Apply DoE, statistical models, and scaleup principles to optimize processes
Lead multivariate analyses and modeling (e.g., PCA, timeseries analytics); develop and deploy reproducible analyses (notebooks/scripts) that inform decisions
Build pragmatic models (mechanistic or hybrid/ML where valuable) and validate with targeted experiments; document assumptions, limits, and outcomes
Leverage digital tools and data systems to improve process understanding and decisionmaking; ensure data provenance and version control
Translate CFD modeling into actionable scaling and control strategies
Collaborate across upstream, downstream, formulation, and analytical teams to align priorities and move decisions forward
Document work in electronic lab notebooks and author highquality technical reports and decision memos
Support tech transfers and regulatory filings with clear, traceable documentation
Drive innovation by evaluating new bioprocess technologies and modeling approaches; create reusable templates and analysis pipelines to raise team velocity
Basic Qualifications
Bachelor's degree in Biochemistry, Molecular Biology, Biotechnology, Chemical Engineering, Biological Engineering, Biomedical Engineering, or a related field, and 4+ years of relevant industry experience; or
Master's degree in a relevant field and 1+ years of relevant industry experience; or
PhD in a relevant field with applicable research experience and/or industry experience.
DoE and multivariate analysis literacy; ability to design, run, and interpret statistically sound studies
Working knowledge of scientific computing/data analysis tools (e.g., Python, R, MATLAB, or equivalent) sufficient to run, adapt, and interpret analyses; capacity to ramp quickly
Experience producing reproducible analysis workflows (e.g., notebooks/scripts) and translating insights into experimental changes or control strategies
Preferred Qualifications
Strong upstream bioprocess foundation: cell culture and bioreactor operation (fedbatch, perfusion)
Scale-up/scale-down fluency and mass transfer fundamentals
Exposure to mechanistic/kinetic modeling (e.g., Monodtype kinetics) and practical ML; ability to connect model insights to biology
Familiarity with data systems and governance (ELN/LIMS, data provenance, version control) is a plus
Clear, firstprinciples reasoning; can explain assumptions and design validation experiments
Success bridging bench science, process engineering, and data science; strong communication and organization
Full time
Regular
Colleague
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