Data Scientist

Job Description The Data Scientist will design and maintain data pipelines connecting manufacturing sensor systems to enterprise platforms, manage the TRISO manufacturing ontology, and ensure data quality and traceability. The role includes integrating MES systems, developing factory simulations for cost and throughput optimization, and building machine learning models for process analysis and optimization. Candidates must have strong programming skills in Python and SQL, experience with data pipelines and industrial data systems, and expertise in DOE, statistical process control, and uncertainty quantification. Experience in simulation, ML, or process optimization is required, along with the ability to communicate insights to leadership. A BS or MS in a quantitative field and 5+ years of applied data science experience (including manufacturing environments) are required. This is on-site five days a week. Salary ranges from 115K-135K. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements Python + SQL; production-grade coding practices; sensor-to-enterprise pipeline experience (SCADA/OPC-UA style industrial data). Ability to translate results to leadership.

Experience with at least two:

discrete-event simulation, surrogate modeling, physics-informed ML, process optimization; ML models for manufacturing states. BS/MS quantitative field or 5+ years applied DS/comp engineering 3+ in manufacturing/process industry.