Remote Operations Research Analyst – Nationwide – Join a Data‑Driven Innovation Team

“`html

Are you a problem‑solver who thrives on turning complex data into actionable strategies? Our fully remote Operations Research Analyst position lets you work from anywhere in the United States while partnering with industry‑leading experts to drive optimization across supply chain, finance, and product development. Bring your quantitative expertise to a fast‑growing tech‑focused company and see your models make real‑world impact.

Salary Range

Estimated compensation: $70,000 – $95,000 USD per year, plus performance‑based bonuses and equity options.

About the Role

As a Remote Operations Research Analyst, you will be the analytical engine behind our strategic decisions. You’ll collaborate with cross‑functional teams—including product managers, engineers, and senior leadership—to design, develop, and implement mathematical models that solve high‑stakes business problems. This fully remote role offers flexibility, autonomy, and the chance to influence company‑wide initiatives from the comfort of your home office.

Key Responsibilities

• Develop and validate linear, integer, stochastic, and simulation models to optimize inventory, logistics, pricing, and resource allocation.
• Translate business requirements into quantitative frameworks, ensuring models align with strategic goals.
• Analyze large data sets using Python, R, or MATLAB; extract insights and present findings in clear, executive‑ready visualizations.
• Collaborate with data engineers to integrate model outputs into production pipelines and dashboards.
• Conduct scenario analysis and sensitivity testing to support risk‑management decisions.
• Document methodologies, assumptions, and results to maintain a knowledge base for future projects.

Requirements

• Bachelor’s or Master’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, or a related quantitative field.
• 2+ years of professional experience building and deploying optimization models in a business environment.
• Proficiency in at least one modeling language or library (e.g., Gurobi, CPLEX, Pyomo, JuMP).
• Strong programming skills in Python, R, or MATLAB; experience with SQL and data extraction tools.
• Excellent communication skills—ability to convey complex analytical concepts to non‑technical stakeholders.
• Self‑starter attitude with proven success working independently in a fully remote setting.

Preferred Qualifications

• Ph.D. in a quantitative discipline.
• Experience in supply chain optimization, revenue management, or financial forecasting.
• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
• Certificates such as CPIM, Six Sigma, or PMP.

Benefits & Perks

• 100% remote work – set your own schedule within U.S. time zones.
• Competitive salary with quarterly performance bonuses.
• Equity participation in a high‑growth tech company.
• Comprehensive health, dental, and vision coverage.
• Generous PTO, paid parental leave, and a flexible holidays policy.
• Professional development stipend for courses, conferences, and certifications.
• Home office allowance (up to $1,500) for ergonomic furniture, monitors, and high‑speed internet.

About Our Company

We are a data‑centric, venture‑backed startup that empowers Fortune 500 brands with cutting‑edge optimization solutions. Our mission is to turn big data into smarter decisions, and we do it by fostering a culture of curiosity, collaboration, and continuous learning. With a fully distributed workforce, we value results over location, and we invest heavily in the tools and training that help our team members thrive.

How to Apply

If you’re ready to leverage your operations research expertise to shape strategic outcomes at a remote‑first company, please submit your resume, a cover letter highlighting a recent optimization project, and any relevant portfolio links (GitHub, Kaggle, etc.) to careers@yourcompany.com. Qualified candidates will be contacted for a virtual interview process that includes a technical case study and a culture fit discussion.

“`