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Data Science Phd Research Jobs (NOW HIRING)

Caris Life Sciences

Manager - Data Science

Tempe, AZ · On-site

... research, product development, commercial initiatives, and customer-facing priorities. This role ... PhD in data science, statistics, biostatistics, computer science, computational biology ...

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This role is designed for new PhD graduates or early‑career researchers interested in applying ... This is a full‑stack data science role, involving model development, analysis, and writing ...

Caris Life Sciences

Manager - Data Science

Tempe, AZ · On-site

... research, product development, commercial initiatives, and customer-facing priorities. This role ... PhD in data science, statistics, biostatistics, computer science, computational biology ...

Formation Bio

Director, Data Science

Boston, NY

$235K - $307K/yr

Collaborate cross-functionally with clinical, technical, and research teams * Present complex ... PhD in computational sciences or life sciences * 7+ years of post-academic experience in life ...

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Data Science Phd Research information

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$37.5K

$122.7K

$196.5K

How much do data science phd research jobs pay per year?

As of Sep 13, 2026, the average yearly pay for data science phd research 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 a data science PhD research?

A Data Science PhD research position involves conducting in-depth, original research in the field of data science, often within a university or academic setting. Researchers in this role work on advanced topics like machine learning, statistical modeling, big data analytics, and artificial intelligence. The goal is to push the boundaries of knowledge in data science, publish academic papers, and contribute to solving complex problems using data-driven approaches. Such positions typically require strong analytical, programming, and mathematical skills, as well as the ability to communicate findings through publications and presentations.

What are some common challenges faced by data science PhD researchers when collaborating with interdisciplinary teams?

Data Science PhD researchers often work with teams from diverse fields such as engineering, medicine, or social sciences. A common challenge is bridging the gap between technical concepts and domain-specific knowledge, which requires strong communication skills and adaptability. Additionally, aligning research goals and expectations across disciplines can be complex, as each field may have different methodologies and success metrics. Overcoming these challenges helps foster innovative solutions and broadens the impact of your research.

What are the key skills and qualifications needed to thrive as a data science PhD researcher, and why are they important?

To thrive as a Data Science PhD Researcher, you need expertise in statistical analysis, machine learning, programming (often Python or R), and a solid academic background in computer science, mathematics, or a related field. Familiarity with data visualization tools, big data platforms (like Hadoop or Spark), and version control systems, as well as relevant publications or conference presentations, is typically expected. Strong analytical thinking, problem-solving abilities, and effective communication skills help researchers excel and collaborate within interdisciplinary teams. These skills enable researchers to drive innovative discoveries, communicate findings clearly, and contribute impactful solutions to complex data-driven problems.

What is the difference between Data Science Phd Research vs Data Analyst?

AspectData Science Phd ResearchData Analyst
Required CredentialsPhD in Data Science, Statistics, or related fieldBachelor's or Master's in related fields
Work EnvironmentAcademic, research institutions, or R&D departmentsBusiness, corporate, or consulting firms
Employer & Industry UsagePrimarily academia, research labs, or specialized R&D teamsBusiness analytics, marketing, finance, and operations

Data Science Phd Research involves advanced research, theoretical development, and academic publishing, often in academic or research settings. In contrast, Data Analysts focus on interpreting existing data to generate actionable insights for businesses. While both roles require strong analytical skills, the PhD research role emphasizes deep theoretical knowledge and experimentation, whereas Data Analysts prioritize practical data handling and reporting.

What are popular job titles related to Data Science Phd Research jobs?

For Data Science Phd Research jobs, the most frequently searched job titles are:

Infographic showing various Data Science Phd Research job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% 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 2 days ago. 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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