As a Senior Data Scientist at MetOx International, you will lead advanced analytics, modeling, and machine learning efforts across our manufacturing operations. You will partner closely with R&D, process engineering, quality, and operations to translate complex process challenges into data-driven insights that improve yield, quality, and scalability.
Requirements
- Develops and deploys statistical models for process characterization, optimization, and quality control in superconductor manufacturing.
- Designs and executes design of experiments (DOE) to identify critical process parameters and optimize production outcomes.
- Implements statistical process control (SPC) methodologies including multivariate control charts and process capability analysis.
- Conducts root cause analysis using advanced statistical techniques combined with process engineering knowledge.
- Builds physics-informed models that combine first-principles engineering with machine learning approaches.
- Develops predictive models for yield optimization, defect detection, and predictive maintenance.
- Applies time-series analysis and forecasting for process monitoring and anomaly detection.
- Implements computer vision and machine learning solutions for automated quality inspection.
- Applies advanced mathematical techniques including optimization theory, differential equations, and numerical methods to solve complex manufacturing challenges.
- Develops digital twins and process simulation models for scenario analysis and process improvement.
- Performs multivariate statistical analysis to understand complex interactions in manufacturing processes.
- Builds decision support tools using mathematical optimization for production planning and resource allocation.
- Designs and implements scalable data pipelines for real-time process monitoring across manufacturing operations.
- Integrates data from multiple sources including SCADA systems, MES platforms, databases, and sensor networks.
- Develops automated reporting systems for KPI tracking, process drift detection, and quality metrics.
- Establishes best practices for data governance, version control, and reproducible research.
- Leads cross-functional data science projects involving R&D, process engineering, quality, and operations teams.
- Mentors junior data scientists and engineers on statistical methods, machine learning, and best practices.
- Translates complex process engineering challenges into tractable data science problems.
- Communicates analytical findings and recommendations to technical and executive stakeholders.
- Drives adoption of data-driven decision-making and advanced analytics across the organization.
Benefits
- Health, dental, and vision available on the first day of employment
- 401(k) match
- Paid parental leave & adoption assistance
- Educational reimbursement
