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Operations Research Jobs in Ontario (NOW HIRING)

Summary: Summary We are seeking a Senior R&D Operations Specialist to help scale the operating systems, planning rhythms, and cross-functional coordination that enable Clio's Product, Design ...

Quantitative background - includes degrees in Mathematics, Statistics, Econometrics, Financial Engineering, Operations Research, Computer Science and Physics. * Programming proficiency with at least ...

Lead and support capability gap analyses, capability and capacity requirements against operational demand and use cases. * Lead and support the identification of research requirements to close ...

New

Working closely with senior leadership, Finance, R&D, Product Development, and Operations, the Project Coordinator will coordinate project activities, collect and organize information from multiple ...

Technology Research Analyst

Ottawa, ON · On-site

CA$111K - CA$140K/yr

Understanding of the factors that influence technology decisions, including operational, safety ... Ability to translate research findings into practical insights that support technology planning ...

Responsibilities also include supporting lab operations such as inventory management, equipment ... research outcomes. The successful applicant will work in the Buechler Lab (www.buechlerlab.com)

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Operations Research information

See Ontario salary details

$26.5K

$91.1K

$175K

How much do operations research jobs pay per year?

As of Aug 3, 2026, the average yearly pay for operations research in Ontario is $91,135.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,000.00 and $111,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an operations research analyst, and why are they important?

To thrive as an Operations Research Analyst, you need strong quantitative analysis, mathematical modeling, and problem-solving skills, typically supported by a degree in mathematics, engineering, or a related field. Familiarity with programming languages (such as Python or R), advanced Excel, and optimization software like CPLEX or Gurobi is often required. Outstanding communication, critical thinking, and teamwork abilities help translate complex data insights into actionable recommendations for stakeholders. These skills ensure effective analysis, informed decision-making, and successful implementation of solutions in complex organizational environments.

What can I do with an operations research degree?

An operations research degree prepares individuals for roles such as operations analyst, supply chain manager, or data analyst, focusing on optimizing processes and decision-making using mathematical modeling and analytical tools. Graduates often work in industries like manufacturing, logistics, finance, and consulting, utilizing skills in statistics, programming, and problem-solving. Certifications in project management or data analysis can enhance career prospects.

What does an operations researcher do?

An operations researcher analyzes complex systems and processes to improve efficiency and decision-making using mathematical models, statistics, and optimization techniques. They often work with data analysis tools and develop algorithms to solve problems in logistics, supply chain, manufacturing, and other operational areas.

What is operations research?

Operations research is a discipline that uses advanced analytical methods, such as mathematical modeling, statistics, and algorithms, to help organizations solve complex problems and make better decisions. Professionals in this field analyze data and systems to optimize processes, improve efficiency, and reduce costs. Operations research is applied in various industries, including logistics, manufacturing, healthcare, and finance, to support strategic planning and operational improvements.

What is the difference between Operations Research vs Data Analyst?

AspectOperations ResearchData Analyst
Required CredentialsBachelor's or master's in operations research, industrial engineering, or related fieldsBachelor's or master's in statistics, mathematics, or data science
Work EnvironmentAnalytical teams, consulting firms, manufacturing, logisticsBusiness, finance, marketing, technology sectors
Employer & Industry UsageSupply chain, transportation, manufacturing, governmentRetail, finance, healthcare, tech companies
Common Search & ComparisonOperations Research vs Data Analyst

Operations Research and Data Analysts both analyze data to improve decision-making, but Operations Research focuses on complex optimization and modeling for large systems, while Data Analysts interpret data trends for business insights. Their roles often overlap but serve different strategic purposes in organizations.

What are the qualifications to get a job in operations research?

The qualifications to get a job in operations research typically include a bachelor’s degree and strong technical and mathematical skills. Data science, statistics, applied math, and engineering are all good subjects to study in college. It is also useful to have a working knowledge of the specific industry in which you work, such as logistics and delivery, healthcare, or business. More complex positions often require advanced degrees. In addition to these formal qualifications, programming experience with R or other statistical software and strong analytical skills are essential.

Does operations research pay well?

Operations research analysts typically earn competitive salaries, with median wages above the national average for many industries. Salaries vary based on experience, education, and location, and professionals often work with data analysis, optimization tools, and statistical software. Advanced skills and certifications can lead to higher compensation.

What are some typical challenges faced by professionals in operations research, and how can they be addressed?

Operations Research professionals often encounter challenges such as working with incomplete or imperfect data, translating complex mathematical models into actionable business solutions, and communicating technical findings to non-technical stakeholders. Successfully addressing these challenges involves collaborating closely with subject matter experts, utilizing robust data validation techniques, and developing strong communication skills to clearly convey results and recommendations. Additionally, staying updated on the latest optimization tools and methodologies can help streamline problem-solving processes.
What are the most commonly searched types of Operations Research jobs in Ontario? The most popular types of Operations Research jobs in Ontario are:
What job categories do people searching Operations Research jobs in Ontario look for? The top searched job categories for Operations Research jobs in Ontario are:
What cities in Ontario are hiring for Operations Research jobs? Cities in Ontario with the most Operations Research job openings:
Infographic showing various Operations Research job openings in Ontario as of July 2026, with employment types broken down into 86% Full Time, 12% Part Time, 1% Temporary, and 1% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $91,135 per year, or $43.8 per hour.

Other

Re-posted 9 days ago


Job description

We are currently looking for highly talented individuals with a history of exceptional academic and/or industry achievement who are interested in working in a fast paced, stimulating and dynamic environment.

Primary Responsibilities:

  • Develop, modify, optimize, test and implement real time quantitative trading models and strategies.
  • Perform statistical analysis of historical and current financial market data.
  • Research strategies in equities, futures, fixed income, and other asset classes.
  • Generate new indicator ideas.

Requirements:

  • PhD or Masters in Mathematics, Statistics, Physics or Operations Research.
  • Must possess expert level C/C++ programming skills.
  • Incredibly strong problem solving and analytical skills.
  • Time series analysis and statistical modeling experience.
  • Some financial experience desired but not required.
  • Must be a strong self-starter and able to work well independently.