Operations Research & Applied Mathematics Specialist

$50/hr

rate as listed

Workload: ~15h/week
Engagement: Project-based
Location: Worldwide
Field: Sciences

Create research-level operations research and applied mathematics problems grounded in real operational data. This is remote, task-based contract work requiring Python knowledge, clear technical writing and independent execution.

The work

You will design research-level problems that test or train AI models, using experience from systems you have modeled or optimized. Relevant work may include supply chains, scheduling, simulation and physical processes, with an emphasis on realistic data, constraints, assumptions and solution methods.

What the platform screens for

The screen focuses on whether you can describe specific optimization or modeling work under follow-up, including the formulation, data limitations, validation method and operational outcome. Hands-on work with real data is preferred over purely theoretical experience. A Master's or PhD with industry optimization or modeling work is preferred, as are public code, a thesis, papers or prior AI evaluation and data annotation work.

Technical expectations

Working knowledge of Python is required. Gurobi or similar solvers are a plus. You should be able to write an original problem, define a defensible answer or evaluation rubric, document assumptions and identify when a proposed solution is mathematically valid but operationally unusable.

Contract logistics

The work is fully remote and completed independently on a flexible, task-based schedule. Tasks are described as taking about six hours, with no fixed weekly commitment or cap on accepted work. Contractors must be able to work without visa sponsorship, and accepted experts complete background and identity verification.

Pay band: $50/hr

What they look for

Hands-on optimization or modeling with real operational data
Working knowledge of Python
Operations research or applied mathematics problem formulation
Validation of optimization, simulation or mathematical models
Clear technical writing and documentation
Independent management of task-based work

Included with this listing

Interview prep — 10 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: This tests whether your experience includes an identifiable system, actual data sources, a concrete formulation and operational constraints rather than only coursework or abstract theory.
A strong answer: Anchor the answer in one project and state the decision being optimized, the data used, the formulation or simulation approach and how the result was assessed. Distinguish clearly between your own contribution and the work of the wider team.
Where people lose it: Candidates lose points by naming a broad application such as supply-chain optimization without explaining the decision variables, constraints, data granularity or their personal role.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.