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How much do public health data science jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for public health data science in the United States is $40.54, according to ZipRecruiter salary data. Most workers in this role earn between $23.80 and $51.68 per hour, depending on experience, location, and employer.

What is a Public Health Data Science job?

A Public Health Data Science job involves using data analysis, statistical modeling, and programming to study health trends, identify risk factors, and inform public health policies. Professionals in this field work with large datasets from sources like hospitals, public health agencies, and research studies to monitor diseases, improve healthcare interventions, and guide decision-making. They often use tools like Python, R, and SQL for data processing and visualization. Their work supports disease surveillance, health equity analysis, and policy evaluation to improve population health outcomes.

What are the key skills and qualifications needed to thrive in the Public Health Data Science position, and why are they important?

To thrive as a Public Health Data Scientist, you need a strong background in statistics, epidemiology, programming (such as Python or R), and a relevant degree in public health, biostatistics, or a related field. Experience with data visualization tools, statistical software, and knowledge of public health surveillance systems, as well as certifications like Certified Health Data Analyst (CHDA), are valuable. Critical thinking, clear communication, and collaboration are important soft skills for translating complex data into actionable public health insights and working with interdisciplinary teams. These skills ensure that data-driven decisions can improve public health outcomes and inform effective policy and intervention strategies.

What are some common challenges faced in Public Health Data Science roles?

Public Health Data Scientists often encounter challenges such as ensuring data quality, managing large and complex datasets from diverse sources, and dealing with incomplete or inconsistent information. Navigating privacy regulations and maintaining confidentiality of sensitive health data is also a key concern. Additionally, effectively communicating analytical findings to non-technical stakeholders requires both technical expertise and strong interpersonal skills. Overcoming these challenges is essential to generate insights that drive impactful public health decisions and programs.
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Public Health Data Science jobs near you
Infographic showing various Public Health Data Science job openings in the United States as of May 2026, with employment types broken down into 89% Full Time, 4% Part Time, and 7% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution, with an average salary of $84,321 per year, or $40.5 per hour.
Postdoctoral Associate Position, Yale School of Public Health and Department of Biostatistics

Postdoctoral Associate Position, Yale School of Public Health and Department of Biostatistics

Yale University

New Haven, CT • On-site

$49.30K - $66.90K/yr

Full-time

Posted 22 days ago

Yale University rating

8.7

Company rating: 8.7 out of 10

Based on 63 frontline employees who took The Breakroom Quiz

39th of 532 rated colleges and universities

Job description

Description
We are actively recruiting a postdoctoral associate to join the Public Health Data Science and Data Equity (DSDE) research team in the School of Public Health with a primary home in the Department of Biostatistics.
The postdoctoral associate will work with Dr. Bhramar Mukherjee, PhD, the inaugural Senior Associate Dean of Public Health Data Science and Data Equity, Anna M.R. Lauder endowed Professor of Biostatistics, Professor of Chronic Disease Epidemiology, Professor of Statistics and Data Science, with a focus on developing methods and tools for the analysis of electronic health records and real-world healthcare data. There will also be opportunities for collaboration with faculty with experience in cancer and cardiovascular diseases. The position is for one year and is renewable for a second year based on satisfactory performance and progress.
The postdoctoral associate will actively participate in methodological and collaborative research as well as support writing research grants. Professional development will be an integral part of the position. This role enables postdocs to gain expertise in analysis and inference within complex, non-probability observational samples while engaging in exciting applications that harness and integrate data from various sources such as electronic health records, biobanks, registries, etc. The position will also provide a solid foundation to build a research career in academia, government, or industry.
Organization: Yale School of Public Health
Department: Biostatistics
Primary Location: New Haven, CT
Education Level: PhD
Shift: Days, 40 hours/week
Work Modality: Flexible, hybrid working arrangements could be accommodated if needed
Expected Start Date: Flexible, as early as November 1, 2025
Additional information on the Yale School of Public Health, the Department of Biostatistics and the Department of Chronic Disease Epidemiology at the School of Public Health can be found via the links below:
About Us | Yale School Of Public Health
Biostatistics | Yale School of Public Health
Chronic Disease Epidemiology Department | Yale School of Public Health
Qualifications
• Completed doctorate in Biostatistics, Statistics, Data Science, Computer Science, Bioinformatics, or a related field before the start of the appointment
• Strong oral and written communication skills, and the ability to work effectively with a wide range of constituencies in a complex and diverse setting
• Proficiency with statistical computing (e.g., R, Python or C/C++)
• Demonstrated capacity to work both collaboratively and independently
• Strong strategic, analytical, and problem-solving skills
• Strong interpersonal and project management skills to facilitate timely and professional deliverables
• Experience with causal inference, machine learning, and artificial intelligence is desirable
• Experience with clinical, EHR, or biobank data analyses is desirable
Application Instructions
To apply:
Interested individuals should submit a (1) CV, (2) cover letter that addresses their specific interest in this position, skills and experiences directly related to this position, and highlight overall research interests and plan, and (3) contact information for three professional references via Interfolio. Review of applications will begin immediately and will continue until the position is filled.
Please apply online.
Questions regarding this position should be directed to bhramar.mukherjee@yale.edu.

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