ZipRecruiter

Log In

1

Data Science Postdoctoral Fellow Jobs (NOW HIRING)

Stevens

Postdoctoral Fellow

Hoboken, NJ · On-site

$63K - $67K/yr

The Postdoctoral Fellow is responsible for the scientific operations of the laboratory regarding ... market data, and organizational considerations. The final salary will be set considering ...

University of Idaho

Postdoctoral Fellow

Moscow, ID · On-site

$55K/yr

Posting Number SP005254P Position Title Postdoctoral Fellow Division/College College of Science ... Experience in computational data analysis e.g. use of UNIX-based systems, R, Python, or similar ...

University of Idaho Job

Postdoctoral Fellow

Moscow, ID · On-site

$55K/yr

Posting Number SP005254P Position Title Postdoctoral Fellow Division/College College of Science ... Experience in computational data analysis e.g. use of UNIX-based systems, R, Python, or similar ...

Van Andel Institute

Postdoctoral Fellow

Grand Rapids, MI · On-site

$70K/yr

We are committed to inspiring the next generation of scientists and educators. The Van Andel Institute (VAI) is seeking to hire a Postdoctoral Fellow in the Burton Laboratory under the direction of ...

next page

Showing results 1-20

People also search for

All JobsData Science Postdoctoral Fellow Jobs

Data Science Postdoctoral Fellow information

See salary details

$25K

$59K

$83.5K

How much do data science postdoctoral fellow jobs pay per year?

As of Jul 7, 2026, the average yearly pay for data science postdoctoral fellow in the United States is $59,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $66,500.00 per year, depending on experience, location, and employer.

What is the difference between Data Science Postdoctoral Fellow vs Data Scientist?

AspectData Science Postdoctoral FellowData Scientist
Required CredentialsPhD in Data Science, Statistics, or related fieldBachelor's or Master's degree in related field, often with industry experience
Work EnvironmentAcademic or research institutions, labsCorporate, tech companies, startups
Employer & Industry UsageUniversities, research institutes, government agenciesPrivate sector, industry-focused
Common Search & Comparison IntentUnderstanding academic/research roles vs industry rolesCareer transition, industry job expectations

While a Data Science Postdoctoral Fellow focuses on research, publishing, and academic contributions, a Data Scientist applies data analysis and modeling directly to business problems in industry. Both roles require strong analytical skills, but their environments and career paths differ significantly.

How do Data Science Postdoctoral Fellows typically collaborate with interdisciplinary teams in a research setting?

Data Science Postdoctoral Fellows often work closely with researchers from diverse backgrounds such as biology, engineering, or social sciences, depending on the focus of the project. Collaboration usually involves translating complex data analytics into actionable insights, leading or contributing to joint publications, and participating in regular team meetings to discuss research progress. Fellows may also mentor graduate students or assist in grant writing, providing technical expertise in statistical modeling or machine learning. This interdisciplinary environment fosters skill development and can open doors to both academic and industry career paths.

What are the key skills and qualifications needed to thrive as a Data Science Postdoctoral Fellow, and why are they important?

To thrive as a Data Science Postdoctoral Fellow, you need advanced expertise in statistics, machine learning, programming (such as Python or R), and a PhD in a quantitative field. Familiarity with data analysis tools, cloud computing platforms, and version control systems (e.g., Git) is essential, along with experience in specialized software relevant to your research domain. Strong analytical thinking, effective communication, and the ability to work both independently and collaboratively are standout soft skills. These competencies are crucial for conducting innovative research, translating complex data into actionable insights, and driving impactful scientific discoveries.

What is a Data Science Postdoctoral Fellow?

A Data Science Postdoctoral Fellow is a researcher who has completed their doctoral studies and works in a temporary academic or industry position focused on advanced data science research. They typically conduct independent or collaborative research projects, develop new data analysis techniques, and contribute to scientific publications. These fellows often work with large datasets, apply machine learning or statistical methods, and support interdisciplinary teams in solving complex problems. The position helps them further develop their research skills and prepare for future academic or industry roles.
What cities are hiring for Data Science Postdoctoral Fellow jobs? Cities with the most Data Science Postdoctoral Fellow job openings:
What states have the most Data Science Postdoctoral Fellow jobs? States with the most job openings for Data Science Postdoctoral Fellow jobs include:
Infographic showing various Data Science Postdoctoral Fellow job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $59,022 per year, or $28.4 per hour.
Postdoctoral Fellow in Biostatistics and Health Data Science

Postdoctoral Fellow in Biostatistics and Health Data Science

Indiana University

Bloomington, IN • On-site

$45K - $61K/yr

Full-time

Re-posted 16 days ago

Job description

Posting Details
Position Details
Title
Postdoctoral Fellow in Biostatistics and Health Data Science
Specific Title
Appointment Type
Postdoctoral Fellow
Department
IUSM - Biostatistics
Campus
IU School of Medicine Indianapolis
Position Summary
Postdoctoral Researcher to advance research at the intersection of artificial intelligence for healthcare, multimodal data analysis (EHRs, medical imaging, omics, physiological signals, clinical notes), and causal AI (causal inference, discovery, counterfactual reasoning). The successful candidate will collaborate with an interdisciplinary team of computer scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations.
Key responsibilities include:
  • Lead original research in multimodal and causal AI for health; design, implement, and rigorously evaluate algorithms and full pipelines.
  • Build reproducible research pipelines and maintain reliable experiment codebases (prefer Python).
  • Apply causal inference and discovery frameworks to clinical questions.
  • Translate proposed methods and frameworks into real-world clinical workflows.
  • Contribute to grant proposals and research reports.

This is an exciting opportunity to join a fast growing BHDS Department with 36 faculty members and more than 50 professional staff. We are dedicated to excellence in biostatistical, health data science, and informatics research and education. We have an extensive portfolio of research program in related areas. Our NIH funding as principal investigators and co-investigators has been ranked among the top in the nation. The Department currently has an ongoing PhD program in Biostatistics, MS program in Biostatistics, and BS program in Health Data Science.
We have established strong collaborations with both clinical and basic science research departments and divisions and health systems including IU Health and Eskenazi Hospitals as well as strong partnerships with major research institutes and centers including Regenstrief Institute, Center for Computational Biology and Bioinformatics, Indiana Clinical and Translational Science Institute (CTSI), Indiana University Simon Comprehensive Cancer Center, Indiana Institute of Biomedical Research, and Indiana Alzheimer's Disease Research Center. Additional details about the Department and the PhD program are available on our web page: https://medicine.iu.edu/biostatistics.
The Indianapolis Campus is the focal point of health professions education at Indiana University, and the School of Medicine is the country's second largest allopathic medical school. Indianapolis consistently ranks high nationally on many of the "best places to live" lists and has an economy that is growing in the life sciences arena. In addition, it has always been one of the cities with the lowest cost of living. Carmel, Indy's northern neighbor, was recently named as the best mid-sized city in the country.
IUSM is committed to being a welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all throughout the state of Indiana.
Indianapolis is the capital and most populous city in the State of Indiana. It is growing economically thanks to a strong corporate base anchored by the life sciences. Indiana is home to one of the largest concentrations of health sciences companies in the nation. Indianapolis has a sophisticated blend of charm and culture with a wonderful balance of business and leisure. The growing residential base is supported by rich amenities and quality of life - the city possesses a variety of professional sports, arts venues and outdoor recreation areas. Residents of this dynamic city, and surrounding suburbs, enjoy leading educational systems and top-ranked universities, paired with a diverse population. Indianapolis International Airport is a top-ranked international airport, being named "Best Airport in North America" by Airports Council International for many years. For additional information on life in Indy: https://faculty.medicine.iu.edu/relocationThe search will continue until the positions are filled.
Basic Qualifications
Required Qualifications:
  • Ph.D. (by start date) in Computer Science, Biomedical Informatics, Health Data Science, Biostatistics, or a closely related area.
  • Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP.
  • Demonstrated working experience with healthcare data (e.g., EHR, clinical text, imaging, omics).
  • Proficiency in Python and ML tooling (e.g., PyTorch, scikit-learn), version control (Git), and experiment tracking (e.g., Weights & Biases).
  • Excellent written and oral communication skills, and ability to collaborate with multidisciplinary teams.

Preferred Qualifications:
  • Experience with LLMs/foundation models (e.g., clinical NLP, retrieval-augmented generation, instruction tuning) and multimodal transformers.
  • Solid understanding of causal methods (e.g., propensity scores, IPW, matching) and/or causal discovery.
  • Familiarity with data engineering and MLOps (e.g., SQL, Spark, Airflow, Docker, Kubernetes).
  • Knowledge of responsible/ethical AI for health: fairness/equity, interpretability, robustness, privacy (e.g., differential privacy, federated learning).
  • Track record of first-author publications in relevant venues and collaborative open-source contributions.

Department Contact for Questions
Professor Jiang Bian via email at: bianj@regenstrief.org
Additional Qualifications
Special Instructions
Priority Application Review Deadline
Expected Start Date
Posting Number
IUSM-02286-2025

Apply