Operations Research Scientist – W2 (Dallas, TX)

About the role

We are looking for an Operations Research Scientist to design, implement, and maintain the core mathematical optimization model that drives our task‑assignment platform. The role works closely with the OR&AA team, planners, and IT partners to translate complex business rules into high‑impact, testable models.

Key responsibilities

• Develop and maintain a Mixed‑Integer Programming (MIP) model that encodes intricate work‑rule constraints.
• Formulate real‑world business rules as decision variables, linear constraints, and objective functions.
• Drive the model through the FICO Xpress Java API, generate .lp files, and interpret solver logs.
• Tune solver parameters (gap tolerances, thread count, random seed, determinism) and analyze branch‑and‑bound performance.
• Validate and benchmark solutions, debug model issues using data stored in Azure ADLS, and resolve infeasibility problems.
• Build and maintain a Streamlit dashboard (Python) to visualize optimizer outputs.
• Collaborate with a Java engineer to productionize the model and with planners/SMEs to capture and verify rules.
• Leverage AI coding assistants (Claude, Copilot) for rapid prototyping while maintaining code quality.

Required profile

• MS or PhD in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science (optimization) or equivalent.
• Strong experience with MIP modeling, LP/IP theory, and commercial solvers.
• Proven ability to translate complex business logic into optimization formulations.
• Excellent collaborative mindset and willingness to work in a team‑oriented environment.

Required skills

• Mixed‑Integer Programming (MIP) modeling
• FICO Xpress (preferred) or Gurobi, CPLEX, OR‑Tools, Hexaly
• Java programming (model abstraction layer)
• Python programming, including Streamlit for dashboards
• Solver tuning and log analysis
• Azure ADLS data access and analysis
• Use of AI coding agents (Claude, Copilot)
• Version control and high coding standards