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Remote Operations Research Analyst Jobs (NOW HIRING)

Air Force Materiel Command

$92K - $143K/yr

The primary purpose of this position is to serve as an Operations Research Analyst performing professional and scientific work requiring systematic, critical, intensive investigation into a subject ...

The Pennsylvania State University

$96K - $114K/yr

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Operations Research is a multidisciplinary field in which a wide range of analytical methods are ...

The Pennsylvania State University

$96K - $114K/yr

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Operations Research is a multidisciplinary field in which a wide range of analytical methods are ...

Tilda Research

... Research Analyst role for our company. We are based in India and USA and this position will be ... operations experts to reimagine the infrastructure for modern health innovation. We are a San ...

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How much do remote operations research analyst jobs pay per year?

As of Jun 6, 2026, the average yearly pay for remote operations research analyst in the United States is $102,462.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $116,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Remote Operations Research Analyst position, and why are they important?

A Remote Operations Research Analyst requires strong analytical and quantitative skills, usually supported by a degree in mathematics, statistics, operations research, or a related field. Familiarity with optimization software (such as CPLEX or Gurobi), programming languages (like Python or R), and proficiency in data visualization tools are commonly expected; certifications in analytics or data science can be advantageous. Excellent problem-solving ability, attention to detail, and clear written and verbal communication skills help analysts effectively present findings and collaborate virtually. These abilities are critical for successfully analyzing complex systems, delivering actionable insights to organizational leaders, and navigating remote work dynamics.

What does a typical workday look like for a Remote Operations Research Analyst?

As a Remote Operations Research Analyst, your typical day involves collecting and analyzing large datasets, building mathematical models to solve business problems, and generating recommendations based on your findings. You'll frequently coordinate with cross-functional teams via virtual meetings, present analytical results, and refine models based on stakeholder feedback. Much of your work will be independent and deadline-driven, but strong communication ensures alignment with project goals. This remote role offers flexibility, but requires self-motivation and effective time management to balance multiple projects and deliver high-quality insights.

What is a Remote Operations Research Analyst job?

A Remote Operations Research Analyst uses mathematical modeling, statistical analysis, and optimization techniques to solve complex business problems, improve processes, and support decision-making. Working remotely, they analyze data, develop simulations, and provide recommendations to enhance efficiency and effectiveness in various industries. They typically collaborate with teams through virtual meetings and tools, using software like Python, R, or Excel. Their work helps organizations optimize resources, reduce costs, and improve overall performance.

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Remote Operations Research Analyst jobs near you
Operations Research Analyst - AI Trainer

Operations Research Analyst - AI Trainer

DataAnnotation

Little Rock, AR • On-site, Remote

$40/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full-time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, starting at $40+ USD per hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Note: Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #datascience #J-18808-Ljbffr

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