play a key role in transforming factory data into actionable intelligence that directly impacts production performance.
Working across Engineering, Operations, and Quality, lead the development and deployment of predictive analytics solutions that improve yield, reduce variation, and drive smarter decision-making at scale.
Design, deploy, and sustain production-grade machine learning solutions, build intuitive data visualization and statistical analysis tools, and partner closely with stakeholders to turn complex data into clear, actionable insights.
Mentor and guide less experienced data scientists and engineers, helping elevate team capabilities and establish best practices in applied data science.
Act as a technical leader, shaping both solutions and the people delivering them.
Requirements
Typically requires a University degree or equivalent experience and a minimum of 8 years of prior relevant experience or an Advanced Degree in a related field and a minimum of 5 years experience.
Active and transferable U.S. government issued Secret security clearance is required prior to start date.
U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance.
Experience developing in Python (NumPy, SciPy, scikit-learn, scikit-image) for production-grade statistical or machine learning applications (beyond academic examples).
Demonstrated experience deploying, maintaining, and scaling machine learning models in production environments.
Experience with relational database management and SQL development.