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Data scientist vs operations research analyst

The differences between data scientists and operations research analysts can be seen in a few details. Each job has different responsibilities and duties. Additionally, a data scientist has an average salary of $106,104, which is higher than the $74,424 average annual salary of an operations research analyst.

The top three skills for a data scientist include python, data science and visualization. The most important skills for an operations research analyst are operations research, DOD, and python.

Data scientist vs operations research analyst overview

Data ScientistOperations Research Analyst
Yearly salary$106,104$74,424
Hourly rate$51.01$35.78
Growth rate16%23%
Number of jobs106,973154,380
Job satisfaction--
Most common degreeBachelor's Degree, 51%Bachelor's Degree, 67%
Average age4145
Years of experience4-

What does a data scientist do?

A Data Scientist analyzes information from multiple sources in order to gain maximum insight that can give the company a competitive advantage. They work in different domains, including manufacturing, healthcare, education, and finance.

What does an operations research analyst do?

Operations research analysts are responsible for assisting organizations in making better decisions. These professionals work to develop solutions that will aid businesses to operate more efficiently using advanced techniques such as data mining, optimization, and mathematical modeling. They work closely with key organizational stakeholders to stay up-to-date on short-term and long-term business goals. They also conduct research that will give them insights they need to guide decision-makers and develop solutions using predictive modeling, simulations, and statistical analysis.

Data scientist vs operations research analyst salary

Data scientists and operations research analysts have different pay scales, as shown below.

Data ScientistOperations Research Analyst
Average salary$106,104$74,424
Salary rangeBetween $75,000 And $148,000Between $48,000 And $113,000
Highest paying CityRichmond, CAWashington, DC
Highest paying stateCaliforniaMaine
Best paying companyThe CitadelThe Citadel
Best paying industryStart-upProfessional

Differences between data scientist and operations research analyst education

There are a few differences between a data scientist and an operations research analyst in terms of educational background:

Data ScientistOperations Research Analyst
Most common degreeBachelor's Degree, 51%Bachelor's Degree, 67%
Most common majorComputer ScienceMathematics
Most common collegeColumbia University in the City of New YorkUniversity of Southern California

Data scientist vs operations research analyst demographics

Here are the differences between data scientists' and operations research analysts' demographics:

Data ScientistOperations Research Analyst
Average age4145
Gender ratioMale, 79.6% Female, 20.4%Male, 68.2% Female, 31.8%
Race ratioBlack or African American, 4.2% Unknown, 5.4% Hispanic or Latino, 6.9% Asian, 18.8% White, 64.2% American Indian and Alaska Native, 0.6%Black or African American, 13.9% Unknown, 5.9% Hispanic or Latino, 12.4% Asian, 12.9% White, 54.4% American Indian and Alaska Native, 0.6%
LGBT Percentage9%9%

Differences between data scientist and operations research analyst duties and responsibilities

Data scientist example responsibilities.

  • Update, maintain, and manage regional CRM database and records for customers, vendors, and suppliers.
  • Configure and manage JobScope ERP system for a make-to-order/make-to-stock design and manufacturing environment.
  • Lead the analysis in SAS for data integration of mortality data using meta-analysis integration methods.
  • Implement a proximal stochastic gradient descent with a line search to fit a regularize logistic regression in Scala
  • Perform cross-validation-test on linear regression model of data using scikit-learn.
  • Develop python base statistical visualization to provide insights of fuzzy social media data.
  • Show more

Operations research analyst example responsibilities.

  • Manage strategic development initiatives in the branch banking area, using COBOL, TSO, and SAS.
  • Manage timely (business/technology) requirements gathering, project documentation, approvals from governance, QA testing and post-production validation.
  • Redesign the software architecture and develop the system with Java, CPLEX and SQL.
  • Establish price to win in compliance with DoD small business concerns.
  • Use of statistical software and SQL to analyze very large databases.
  • Prepare clear and concise PowerPoint project updates and presentations for high level executives.
  • Show more

Data scientist vs operations research analyst skills

Common data scientist skills
  • Python, 13%
  • Data Science, 10%
  • Visualization, 5%
  • Java, 4%
  • Hadoop, 4%
  • Tableau, 3%
Common operations research analyst skills
  • Operations Research, 20%
  • DOD, 9%
  • Python, 5%
  • Statistical Analysis, 4%
  • C++, 4%
  • Data Analysis, 3%

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