Lead Data Scientist, Operations Research

Sensata Technologies • Attleboro, MA

2d • $119,600 - $164,450

About The Position

The Lead Data Scientist, Operations Research leads optimization, forecasting, and decision modeling for Sensata's operations, initially focused on Supply Chain and extending to Procurement and Engineering. The role converts complex inventory, planning, scheduling, and cost problems into production models that influence how planners, buyers, and engineers make decisions. It establishes data science standards for operations AI use cases and supports enterprise data science needs as priorities arise.

The position leads operations data science modeling from problem framing through production and adoption, builds optimization and forecasting models, sets modeling and validation standards, and works with business stakeholders to ensure models improve inventory, service, and cost outcomes. It also provides technical direction and mentoring to data scientists and AI engineers working on operations use cases.

Requirements

• A university degree, such as a bachelor's degree, or equivalent relevant work experience.
• At least 7 years of experience building optimization, machine learning, and statistical models for operational problems, with models deployed and in sustained use.
• Deep operations research expertise, including linear and mixed-integer programming, constrained optimization, inventory theory, scheduling, and simulation.
• Hands-on experience with optimization solvers and frameworks such as Gurobi, CPLEX, OR-Tools, or Pyomo.
• Strong time-series forecasting skills, including hierarchical and probabilistic methods and rigorous backtesting.
• Strong Python and SQL skills, and comfort working with raw ERP, EDI, and manufacturing data.
• Ability to challenge and influence senior leaders and vendors with evidence.
• Ability to work as a team player in a fast-paced environment and handle multiple competing tasks and demands.
• Strong oral, written, and presentation communication skills.
• Strong organization, planning, and time-management skills.
• Strong personal and professional ethical values and integrity.
• Accountability for achieving goals and standards.
• Proficiency with Microsoft Office programs, including Outlook, Word, PowerPoint, and Excel.
• Strong interpersonal and collaboration skills to work effectively with all levels of the organization, including suppliers and external customers.

Nice To Haves

• Experience in manufacturing, automotive, industrial, or distribution supply chains.
• A master's or PhD in Operations Research, Industrial Engineering, Statistics, Applied Mathematics, or a related field.

Responsibilities

• Oversee the development of innovative product solutions to continuously drive value for customers.
• Lead development project teams by defining data needs and advising on insights into customer challenges.
• Identify valuable data sources and efficient data collection processes.
• Analyze large data sets to discover trends and value-driven insights.
• Lead predictive models and algorithms, and oversee processes and tools for analyzing model performance and data accuracy.
• Communicate complex findings and ideas using data visualization techniques.
• Lead data science modeling and approaches for operations use cases, including Supply Chain, from problem framing through production and adoption.
• Build optimization models for inventory policy, multi-echelon safety stock, item segmentation, capacity and production planning, and lab and test scheduling.
• Build demand forecasting and signal-reliability models for noisy customer and EDI demand.
• Develop should-cost and spend analytics to support Procurement decisions.
• Design empirical tests to evaluate vendor and planning-platform models, and hold vendors to agreed performance thresholds.
• Set standards for modeling, validation, and backtesting; define retraining and monitoring requirements with the AI Platform/MLOps team.
• Work directly with planners, buyers, and business leaders to drive model adoption and improve inventory, service, and cost.
• Provide technical direction and mentoring to data scientists and AI engineers working on operations use cases.

Benefits

• Competitive medical, dental, vision, life, and disability insurance plans.
• Education reimbursement.
• Wellness programs.
• 401(k) retirement plan with Company matching.
• Paid time off, including vacation or flex-time, sick, bereavement, and parental leave.
• Certain positions are eligible for short-term and long-term incentive programs.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior