Data Scientist

• Python + SQL; production-grade coding practices; sensor-to-enterprise pipeline experience (SCADA/OPC-UA style industrial data).
• DOE + SPC + uncertainty quantification; 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; 5+ years applied DS/comp engineering; 3+ in manufacturing/process industry.

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.

Targeting pay $60-68/hr.