Operations Research Engineer - Remote

Remote • Posted 1 hour ago • Updated 1 hour ago
Contract Independent
Contract Corp To Corp
Contract W2
12 Months
Remote
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • WFM

Summary

Role: Operations Research Engineer
Location: Remote
Duration: 12+ Months

What You'll Do
Design, build, and tune workforce scheduling optimization models using Google OR-Tools (or equivalent constraint programming / mixed-integer optimization toolkits).
Translate real-world WFM constraints - shift patterns, skill-based routing, agent availability, service-level targets - into solvable optimization formulations.
Work directly with product and engineering to integrate the optimization engine into the broader WFM platform, consuming live data (call volumes, agent performance, real-time status) from Amazon Connect.
Participate in design discussions and iterate on model performance against real adoption and usability feedback, not just theoretical accuracy.
Document modeling assumptions and tradeoffs clearly enough for a non-OR engineering team to maintain the system long-term.

Required Experience
6 10 years combined experience in operations research, optimization engineering, or applied algorithms - including hands-on production use of OR-Tools or a comparable solver (CPLEX, Gurobi, OptaPlanner).
Demonstrated experience modeling scheduling, rostering, or resource-allocation problems - workforce/contact-center scheduling experience is a strong plus but general scheduling/logistics optimization background is acceptable.
Strong software engineering fundamentals - able to integrate optimization code into a production full-stack platform, not just deliver notebooks or standalone scripts.
Comfortable working in a cloud-native stack (AWS, Kubernetes, Docker).
Must be based in and eligible to work remotely within the United States.

Preferred
Prior Workforce Management (WFM) software development experience.
Familiarity with contact center operations (service levels, shrinkage, Erlang-based staffing models) as context for the optimization work.

Sourcing & Screening Notes (Internal)
Hard requirement seat - do not substitute general "data science" or ML candidates without explicit constraint-programming/solver production experience.
Only 2 seats - prioritize depth of OR-Tools expertise and ability to explain prior scheduling/optimization work concretely over general seniority alone.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91099596
  • Position Id: 9066160
  • Posted 1 hour ago
Contact the job poster
Arunkumar Chinnasamy

Arunkumar Chinnasamy

Recruiter @ Emergere Technologies
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