Remote Operations Research Analyst – United States – Transform Complex Data into Strategic Advantage

Join a forward‑thinking analytics team that turns massive data sets into actionable insights for global clients. As a Remote Operations Research Analyst at Apex Analytics, you’ll design optimization models that drive efficiency, reduce costs, and unlock new revenue streams—all from the comfort of your home office.

About the Role

Apex Analytics is seeking a curious, results‑oriented Operations Research Analyst to build and deploy mathematical models that solve real‑world logistics, supply‑chain, and resource‑allocation challenges. You will collaborate with data engineers, product managers, and client stakeholders to translate business problems into quantitative frameworks, prototype algorithms, and deliver production‑ready solutions. This fully remote position offers the autonomy to shape high‑impact projects while working alongside a diverse, distributed team of analysts and scientists.

Key Responsibilities

• Formulate linear, integer, and stochastic programming models for routing, scheduling, inventory, and workforce optimization.
• Develop custom heuristics and meta‑heuristics (e.g., genetic algorithms, simulated annealing) when exact methods are computationally prohibitive.
• Integrate models into scalable pipelines using Python, Julia, or R, leveraging libraries such as PuLP, OR‑Tools, Gurobi, or CPLEX.
• Conduct rigorous sensitivity analysis and scenario testing to validate model robustness under uncertainty.
• Present findings and recommendations to non‑technical stakeholders through clear visualizations and executive summaries.
• Stay current with emerging OR techniques, machine‑learning hybrids, and cloud‑based optimization services.

Requirements

• Master’s degree (or Ph.D.) in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or a related quantitative field.
• 3+ years of professional experience building and deploying optimization models in a commercial environment.
• Proficiency in Python (NumPy, Pandas, SciPy) and at least one mathematical programming language (AMPL, GAMS, or JuMP).
• Hands‑on experience with commercial solvers (Gurobi, CPLEX, Xpress) and open‑source alternatives (CBC, HiGHS).
• Strong grasp of probability, stochastic processes, and statistical inference for model validation.
• Excellent written and verbal communication skills; ability to translate technical concepts for diverse audiences.
• Legal authorization to work in the United States; this role is open to residents of any U.S. state.

Preferred Qualifications

• Experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes) for model deployment.
• Background in reinforcement learning or simulation‑optimization hybrids.
• Published research or conference presentations in operations research, transportation science, or related domains.
• Familiarity with Agile/Scrum ceremonies and version‑control workflows (Git, GitHub Actions).

Salary Range

$95,000 – $130,000 USD per year, commensurate with experience and geographic differentials.

Benefits & Perks

• 100% remote work with a generous home‑office stipend ($1,200 annually).
• Comprehensive health, dental, and vision coverage for you and dependents.
• 401(k) match up to 5% plus profit‑sharing contributions.
• Unlimited PTO policy encouraging true work‑life balance.
• Annual learning budget ($2,500) for courses, certifications, and conferences.
• Quarterly virtual team‑building events and an annual in‑person retreat (travel covered).

Culture & Values

At Apex Analytics we believe that diverse perspectives fuel better models. Our culture is built on intellectual humility, continuous learning, and radical transparency. We celebrate experimentation—failed hypotheses are treated as data, not setbacks. Collaboration happens asynchronously across time zones, supported by clear documentation and shared notebooks. If you thrive on solving puzzles that matter and want to see your algorithms move the needle for real businesses, you’ll feel at home here.

How to Apply

Interested candidates should submit a resume, a brief cover letter highlighting a recent optimization project, and a link to a public code repository or portfolio (GitHub, GitLab, or personal site). Applications are reviewed on a rolling basis; selected applicants will be invited to a technical screening followed by a virtual panel interview with the analytics leadership team.