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Health Data Science Fellow Jobs (NOW HIRING)

... and data science applications to research centers and healthcare organizations nationally and ... Flexible Spending Accounts: * Healthcare (FSA) * Parking Reimbursement Account (PRK) * Dependent ...

Voloridge Health is dedicated to developing a data-science-driven approach to assess, track, and improve healthspan. Founded in 2023 with the same data science background that has propelled its ...

Voloridge Health is dedicated to developing a data-science-driven approach to assess, track, and improve healthspan. Founded in 2023 with the same data science background that has propelled its ...

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Health Data Science Fellow information

What is the difference between Health Data Science Fellow vs Data Analyst?

AspectHealth Data Science FellowData Analyst
Required CredentialsTypically advanced degrees in health informatics, data science, or related fields; some fellowships may require certificationsBachelor's or master's in data analysis, statistics, or related fields; certifications like CAP or Microsoft Certified Data Analyst are common
Work EnvironmentResearch institutions, healthcare organizations, or academic settings focusing on health data projectsBusiness, healthcare, or tech companies analyzing data to inform decisions
Employer & Industry UsagePrimarily in healthcare, research, and academic sectorsAcross various industries including healthcare, finance, marketing, and technology

In summary, a Health Data Science Fellow focuses on advanced health-related data projects often within research or academic settings, requiring specialized health informatics knowledge. A Data Analyst has a broader role across industries, analyzing data to support business decisions, often with more general data analysis skills.

What is a Health Data Science Fellow?

A Health Data Science Fellow is a professional participating in a specialized fellowship program focused on applying data science techniques to healthcare data. Fellows work on projects involving the analysis of medical, clinical, or public health datasets to derive insights that can improve patient care, hospital operations, or health policy. These programs typically combine mentorship, hands-on experience with real-world datasets, and advanced training in statistics, programming, and machine learning. The role is ideal for individuals with a background in data science, statistics, or health sciences who want to deepen their expertise in health-related applications.

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

To thrive as a Health Data Science Fellow, you need strong analytical skills, proficiency in statistics, and a background in fields like public health, computer science, or bioinformatics, often supported by a relevant degree. Experience with programming languages (such as Python or R), data visualization tools, and familiarity with healthcare data systems are typically required. Excellent problem-solving, communication, and teamwork skills help fellows translate complex data insights into actionable healthcare solutions. These capabilities are crucial for driving data-driven improvements in health outcomes and supporting evidence-based decision-making in medical environments.

What types of projects can a Health Data Science Fellow expect to work on, and how do these contribute to team goals?

Health Data Science Fellows typically engage in projects such as analyzing large-scale healthcare datasets, developing predictive models for patient outcomes, or supporting clinical research with data-driven insights. These projects are often collaborative, involving close work with clinicians, IT professionals, and other data scientists to ensure analyses are relevant and actionable. Fellows contribute by turning complex data into meaningful recommendations that can improve patient care, operational efficiency, or public health initiatives. The role provides a unique opportunity to gain hands-on experience with real-world health data and make a measurable impact within multidisciplinary teams.
More about Health Data Science Fellow jobs
What job categories do people searching Health Data Science Fellow jobs look for? The top searched job categories for Health Data Science Fellow jobs are:
Infographic showing various Health Data Science Fellow job openings in the United States as of June 2026, with employment types broken down into 93% Full Time, 3% Part Time, 3% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.
AAR Data Science Fellow

Part-time

Posted 13 days ago


Job description

Data Science Fellowship

The Policy & Economics (P&E) Division of the Association of American Railroads is pleased to invite applications for the Data Science Ph.D. Fellowship for the year 2025-2026. This fellowship offers a unique opportunity for Ph.D. students or experienced professionals interested in data management, analysis, and visualization projects related to the railroad industry and its regulatory requirements.

About the Fellowship:

The Data Science Fellowship aims to provide data science professionals with hands-on experience and collaborative opportunities to enhance their skills. Successful candidates will work part-time for one year, engaging in activities at the intersection of data science methods and scholarly domains utilizing data science for knowledge discovery and creation. Fellows will contribute to P&E's data modernization effort and will have the opportunity to contribute to AAR's recurring reports and publications, gaining valuable expertise in the railroad industry. The selected candidate will partner with economists and analysts to understand business process flow and the associated data flow, inputs, and outputs to derive a connected design.

Key Details:

  • Part-time appointment (24 hours/week, onsite) for one year with the possibility of appointment extension for another year.
  • Annual stipend commensurate with experience
  • Mentorship and career support provided
  • Opportunity to contribute to data modernization efforts, develop impactful visualizations and dashboards, and gain specialized knowledge of the railroad industry by supporting AAR's recurring reports, ensuring timely delivery and high standards of quality and clarity.