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Data Science Phd Research Jobs (NOW HIRING)

Mayo Clinic

Data Science Analyst

Phoenix, AZ

$99K - $148K/yr

... or research experience in data science will be considered. The preferred candidate will possess a Master's degree or a PhD in a relevant field such as engineering, mathematics, computer science ...

Mayo Clinic

Data Science Analyst

Phoenix, AZ · On-site

... or research experience in data science will be considered. The preferred candidate will possess a Master's degree or a PhD in a relevant field such as engineering, mathematics, computer science ...

Norstella

Director, Data Science

The Team: Our dedicated Data Science team is at the forefront of revolutionizing pharma ... PhD in Computer Science with an AI/ML research focus and publications in top-tier venues

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 Jun 22, 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 position?

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 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 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.
Infographic showing various Data Science Phd Research job openings in the United States as of June 2026, with employment types broken down into 9% Internship, 64% Full Time, 18% Part Time, and 9% Contract. Highlights an 73% In-person, and 27% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Graduate/PhD Research Intern, Machine Learning

Constellation Space

Seattle, WA • On-site

$6.0K - $7.0K/mo

Full-time

Posted 11 days ago

Job description

About Constellation

Constellation is building software to model, predict, and improve satellite network operations. We combine simulation, data/ML workflows, and product-facing platform systems to support better operational decisions.

Role Overview

We are seeking a research-focused ML intern (MS/PhD level) to help advance our modeling and experimentation capabilities. This role is ideal for someone who enjoys turning research ideas into rigorous experiments and high-quality prototypes that can influence real product and platform direction.
Note: This role requires access to ITAR-controlled data, so we need candidates to be U.S. persons (citizen, green card holder, or asylee/refugee).

What You’ll Do

- Design and run ML experiments for forecasting and anomaly/risk prediction in network operations

- Develop and evaluate models using time-series, probabilistic, and simulation-informed approaches

- Improve feature engineering, dataset quality, and evaluation methodology

- Build reproducible research workflows for training, validation, and model comparison

- Communicate findings through clear technical writeups and recommendations

What We’re Looking For

- Currently enrolled in an MS or PhD program (CS, EE, Aerospace, Applied Math, or related)

- Strong low level engineering skills and comfort with scientific/ML tooling (C++, Python, Rust)

- Ability to own projects end-to-end: scoping, implementation, testing, and communication

- Clear written/verbal communication and strong collaboration habits

Nice to Have

- Experience with APIs, cloud infrastructure, or data-intensive systems

- Familiarity with model evaluation, experiment tracking, and reproducibility

- Background in networking, geospatial systems, telecom, or space-tech