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How much do operations research internship jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for operations research internship in the United States is $17.64, according to ZipRecruiter salary data. Most workers in this role earn between $14.66 and $19.23 per hour, depending on experience, location, and employer.

What is an Operations Research Internship?

An Operations Research Internship is a temporary position, often offered to students or recent graduates, where individuals gain hands-on experience applying mathematical, statistical, and analytical methods to help solve real-world business problems. Interns typically work with data analysis, optimization models, simulations, and process improvement projects, supporting decision-making in fields like logistics, supply chain, finance, and manufacturing. The internship provides valuable exposure to industry-standard tools and techniques, and helps interns develop practical skills for a career in operations research or analytics.

What types of projects do Operations Research interns typically work on, and how much autonomy can I expect?

As an Operations Research intern, you can expect to work on data-driven projects such as optimizing business processes, developing simulation models, or analyzing supply chain performance. The work often involves collaborating with cross-functional teams like data analysts, engineers, and business managers to identify inefficiencies and propose actionable solutions. While you'll receive guidance from senior staff, interns are often given ownership of specific tasks or sub-projects and are encouraged to contribute their ideas. This balance of mentorship and autonomy helps interns build practical skills and gain exposure to real-world organizational challenges.

What are the key skills and qualifications needed to thrive as an Operations Research Intern, and why are they important?

To thrive as an Operations Research Intern, you need a strong background in mathematics, statistics, and analytical problem-solving, often supported by coursework in operations research or industrial engineering. Familiarity with programming languages like Python or R, optimization tools such as CPLEX or Gurobi, and data analysis software like Excel or MATLAB is typically required. Effective communication, critical thinking, and teamwork are essential soft skills for conveying complex findings and collaborating with multidisciplinary teams. These skills ensure interns can analyze real-world problems, present actionable insights, and support data-driven decision-making within organizations.
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Operations Research Internship jobs near you
Infographic showing various Operations Research Internship job openings in the United States as of July 2026, with employment types broken down into 9% Internship, 1% As Needed, 68% Full Time, 20% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution, with an average salary of $36,693 per year, or $17.6 per hour.

New Grad Full-Time Quantitative Researcher

WallStreetQuants

New York, NY

Full-time

Posted 10 days ago

Job description

About the Role

An NYC based hedge fund is seeking a highly motivated and intellectually curious New Grad Quantitative Researcher to join the team full time. This role is ideal for recent graduates who enjoy solving complex problems using mathematics, statistics, programming, and data-driven analysis.

As a Quantitative Researcher, you will work at the intersection of financial markets, statistical modeling, and technology. You will collaborate with traders, developers, and other researchers to identify patterns in market data, develop predictive models, test trading hypotheses, and support the creation of quantitative strategies.

This is an excellent opportunity for a new graduate who is analytical, creative, and excited to apply rigorous research methods to real-world financial markets.

Requirements

Responsibilities
  • Conduct quantitative research to identify signals, patterns, and inefficiencies in financial markets.
  • Analyze large and complex datasets, including market data, alternative data, and time-series data.
  • Develop, test, and refine statistical models, predictive signals, and trading strategies.
  • Design and run backtests, simulations, and experiments to evaluate research ideas.
  • Collaborate with traders and developers to translate research findings into production-ready tools and strategies.
  • Monitor model performance and contribute to ongoing strategy improvement.
  • Apply techniques from statistics, machine learning, optimization, probability, and econometrics to solve trading-related problems.
  • Present research findings clearly to technical and non-technical stakeholders.
  • Stay current on market behavior, quantitative methods, and emerging research relevant to trading and investing.
Qualifications
  • Recent graduate or upcoming graduate from a Bachelor's, Master's, PhD, or equivalent program.
  • Degree or strong demonstrated experience in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Physics, Economics, Finance, Data Science, Operations Research, or a related discipline.
  • Strong foundation in probability, statistics, linear algebra, optimization, or machine learning.
  • Programming experience in Python, R, C++, Java, Julia, MATLAB, or a similar language.
  • Experience working with data through coursework, research, internships, projects, or independent study.
  • Strong analytical thinking, problem-solving ability, and attention to detail.
  • Ability to communicate complex ideas clearly and work collaboratively across teams.
  • Interest in financial markets, trading, investing, or data-driven decision-making.
Preferred Qualifications
  • Research, internship, or project experience involving statistical modeling, machine learning, time-series analysis, forecasting, optimization, or quantitative finance.
  • Experience with Python data science libraries such as pandas, NumPy, SciPy, scikit-learn, PyTorch, TensorFlow, or statsmodels.
  • Familiarity with SQL, large-scale data processing, cloud tools, or distributed computing.
  • Exposure to financial instruments such as equities, futures, options, fixed income, FX, commodities, or digital assets.
  • Experience with backtesting, simulation, portfolio construction, or risk modeling.
  • Participation in math competitions, programming competitions, research publications, Kaggle, hackathons, trading competitions, poker, chess, or other analytical competitions.

Benefits

What We Offer
  • Full-time role designed for new graduates.
  • Structured training and mentorship from experienced quantitative researchers, traders, and engineers.
  • Opportunity to work on impactful research used in real-time trading and investment decisions.
  • Exposure to financial markets, strategy development, data science, and trading infrastructure.
  • A collaborative, intellectually rigorous environment where research quality and strong ideas are valued.
  • Early ownership of meaningful research projects.
  • Competitive compensation and benefits.

Apply