Operation Research Data Scientist information
See salary details
$66.4K - $80.9K
6% of jobs
$80.9K - $95.3K
9% of jobs
$100K is the 25th percentile. Wages below this are outliers.
$95.3K - $109.8K
15% of jobs
The median wage is $119.4K / yr.
$109.8K - $124.2K
22% of jobs
$132.2K is the 75th percentile. Wages above this are outliers.
$124.2K - $138.7K
32% of jobs
$138.7K - $153.1K
3% of jobs
$153.1K - $167.6K
4% of jobs
$167.6K - $182K
1% of jobs
$182K - $196.5K
2% of jobs
How much do operation research data scientist jobs pay per year?
As of Sep 4, 2026, the average yearly pay for operation research data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.
An Operations Research Data Scientist is a professional who combines advanced analytical, statistical, and mathematical modeling techniques to solve complex business problems and optimize processes. They utilize tools from operations research, such as linear programming, simulation, and optimization algorithms, alongside data science skills like machine learning and data analysis. Their goal is to help organizations make data-driven decisions that improve efficiency, reduce costs, and enhance overall performance.
Operation Research Data Scientists often work closely with colleagues from engineering, product management, and business analytics to translate complex mathematical models into actionable strategies. They participate in regular meetings to align on project goals, share analytical findings, and integrate optimization algorithms into existing systems. Collaboration involves clear communication of technical concepts to non-technical stakeholders and iteratively refining solutions based on feedback, ensuring that their work delivers tangible value to organizational objectives.
To thrive as an Operations Research Data Scientist, you need a solid background in mathematics, statistics, optimization, and computer science, often supported by an advanced degree in a quantitative field. Proficiency with programming languages such as Python or R, experience with optimization libraries (like Gurobi or CPLEX), and familiarity with data analysis platforms are typically required. Strong problem-solving abilities, communication skills, and business acumen set standout professionals apart in this role. These competencies are crucial for developing actionable solutions to complex business problems and effectively communicating insights to stakeholders.
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