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University Research Data Scientist Jobs (NOW HIRING)

University of Rochester

$26.90 - $37.66/hr

R269057As a community, the University of Rochester is defined by a deep commitment to Meliora ... Contributes to the scientific research.* Adheres to defined application development life-cycle ...

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$37.5K

$122.7K

$196.5K

How much do university research data scientist jobs pay per year?

As of Sep 12, 2026, the average yearly pay for university 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.

What is the difference between University Research Data Scientist vs Data Analyst?

AspectUniversity Research Data ScientistData Analyst
Required CredentialsMaster's or PhD in Data Science, Statistics, or related fieldBachelor's or Master's in Data Analysis, Statistics, or related field
Work EnvironmentAcademic research settings, universities, research labsBusiness, corporate, or government organizations
Employer & Industry UsageUniversities, research institutions, academic projectsCompanies, marketing, finance, healthcare
Common Search & ComparisonYesYes

The main difference between a University Research Data Scientist and a Data Analyst lies in their work environment, credentials, and focus. University Research Data Scientists typically work in academic or research settings with advanced degrees, focusing on scientific research and data modeling. Data Analysts often work in business environments, analyzing data to inform decision-making. Both roles require strong analytical skills, but their applications and industries differ significantly.

What are popular job titles related to University Research Data Scientist jobs?

For University Research Data Scientist jobs, the most frequently searched job titles are:

Infographic showing various University Research Data Scientist job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Research Data Scientist, Merchant Shopping

Mountain View, CA • On-site

Socket.dev
Network Security • 1 - 10 employees
Learn more about Socket.devexternal

Other

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

Job description

Minimum qualifications:
  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  • 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
Preferred qualifications:
  • 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
About the job:

The Merchant Data Science team is a group of data scientists (US, London, Zurich) within the Merchant Shopping Organization. We work on building scalable data products that empower data-driven decision-making.

We are looking for a passionate, engineering-minded Data Scientist who is eager to innovate on data science using genAI tools and build durable, impactful data products.

In this role, you will need to be a full-stack expert who can bridge the gap between software engineering, data engineering, and data science.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:
  • Build innovative data products like self-serve tools, experiment frameworks, autorater and human evaluations.
  • Operate and contribute towards building a data science team that has engineering style work quality.
  • Provide data-driven perspectives on product direction and opportunities. Define, track, and analyze key metrics and attribution mechanisms to guide product development.
  • Conduct in-depth research and analyses to identify the most significant opportunitiesfor improving the Shopping Graph.
  • Communicate complex findings and recommendations clearly and effectively.
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