Remote Operations Research Analyst – Join a Fast‑Growing Analytics Team Shaping Data‑Driven Decisions

We are seeking a detail‑oriented Operations Research Analyst to apply advanced mathematical modeling and optimization techniques to solve complex business challenges. In this fully remote role, you will collaborate with cross‑functional teams to turn data into actionable insights that drive efficiency and profitability.

About the Role

As an Operations Research Analyst, you will design and implement quantitative models that support strategic decision‑making across supply chain, logistics, and finance functions. You will work closely with stakeholders to translate business problems into mathematical formulations, run simulations, and present findings through clear visualizations and reports. This position offers the autonomy to explore innovative methodologies while delivering measurable impact on cost reduction and performance improvement.

Key Responsibilities

• Develop optimization models (linear, integer, stochastic) to improve resource allocation and scheduling.
• Conduct simulation studies to evaluate process changes and risk scenarios.
• Analyze large datasets using statistical tools and programming languages such as Python, R, or Julia.
• Validate model outputs against historical data and refine assumptions for greater accuracy.
• Prepare technical documentation and executive‑level presentations that communicate insights and recommendations.
• Partner with IT and data engineering teams to ensure data pipelines are reliable and models are production‑ready.
• Stay current with emerging OR techniques and advise the organization on adopting new analytical capabilities.

Requirements

Education and Experience

• Bachelor’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, or a related field; Master’s preferred.
• Minimum of three years of hands‑on experience building and deploying optimization or simulation models in a business environment.
• Proven track record of delivering quantifiable results, such as cost savings or process time reductions.

Technical Skills

• Proficiency in optimization solvers (Gurobi, CPLEX, XPRESS) and modeling languages (AMPL, Pyomo, JuMP).
• Strong programming skills in Python (NumPy, SciPy, pandas) or R; familiarity with Julia is a plus.
• Experience with statistical analysis, hypothesis testing, and regression modeling.
• Ability to create clear visualizations using Tableau, Power BI, or matplotlib/seaborn.
• Solid understanding of SQL and experience working with relational databases.

Soft Skills

• Excellent problem‑solving mindset with a curiosity for digging into root causes.
• Strong communication abilities to translate technical findings for non‑technical audiences.
• Ability to manage multiple projects independently while meeting deadlines.
• Collaborative team player who thrives in a remote, fast‑paced setting.

Benefits

• Competitive salary range: $78,000 – $102,000 USD per year, based on experience and location.
• Fully remote work flexibility with a stipend for home office setup.
• Comprehensive health, dental, and vision plans.
• 401(k) with company match and equity‑based incentives.
• Generous paid time off, parental leave, and wellness programs.
• Access to professional development budgets, conference attendance, and certification reimbursements.
• Regular virtual team‑building events and an inclusive company culture.

What You’ll Achieve in the First Six Months

1. Deliver at least two production‑ready optimization models that reduce operational costs by a minimum of 5%.
2. Streamline the data preparation pipeline, cutting model turnaround time from days to hours.
3. Present quarterly insights to senior leadership, influencing strategic initiatives.
4. Mentor junior analysts and help establish best‑practice modeling standards across the team.