Description
The role is a hands-on optimization scientist responsible for developing, maintaining, tuning, and validating mixed-integer programming models for task assignment. The scientist translates business rules into linear constraints and objectives, uses FICO Xpress or similar commercial solvers, debugs infeasibility and data-quality issues using Azure ADLS, maintains a Java-based solver abstraction and a Streamlit dashboard, and collaborates with Java engineers, planners, and business stakeholders. The position requires an MS or PhD in operations research, industrial engineering, applied mathematics, computer science, or a related field, along with strong MIP, solver, Java, Python, and data-analysis capabilities.
