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Volunteering Public Health Data Science Jobs (NOW HIRING)

Data Scientist

Queens, NY · On-site

$126K/yr

The Center for Population Health Data Science (CPHDS)- launched in October of 2023- aims to catalyze critical data modernization work and enable the agency to make progress toward linking public ...

Advanced degree (MS or PhD) in Data Science, Epidemiology, Public Health, Biostatistics, or related ... Voluntary Life and AD&D Insurance * Health Savings Account, Health Care & Dependent Care Flexible ...

The Center for Population Health Data Science (CPHDS)- launched in October of 2023- aims to catalyze critical data modernization work and enable the agency to make progress toward linking public ...

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Volunteering Public Health Data Science information

How do volunteering public health data scientists typically contribute to interdisciplinary teams?

Volunteering public health data scientists often work alongside epidemiologists, health educators, policy advisors, and community outreach coordinators. Their main role is to analyze and interpret health-related data, helping the team identify trends, measure intervention outcomes, and inform decision-making. They regularly collaborate by presenting findings in accessible formats, offering technical support on data collection methods, and recommending data-driven strategies to improve public health initiatives. This collaborative environment fosters learning and broadens the impact of data-driven solutions within community health projects.

What are the key skills and qualifications needed to thrive as a Volunteering Public Health Data Scientist, and why are they important?

To thrive as a Volunteering Public Health Data Scientist, you need a strong background in statistics, epidemiology, and data analysis, often supported by a degree in public health, statistics, or a related field. Proficiency with data analysis tools such as R, Python, and public health databases, as well as familiarity with data visualization software, is typically required. Excellent communication, teamwork, and problem-solving skills are crucial for translating complex data into actionable insights and collaborating with diverse stakeholders. These competencies are essential for effectively supporting public health initiatives and ensuring data-driven decisions that improve community health outcomes.

What is the difference between Volunteering Public Health Data Science vs Public Health Data Analyst?

AspectVolunteering Public Health Data SciencePublic Health Data Analyst
Required CredentialsOften no formal credentials; relevant skills preferredBachelor's or higher in public health, data science, or related fields
Work EnvironmentVolunteer settings, non-profits, community projectsGovernment agencies, healthcare organizations, research institutions
Employer & Industry UsageNon-profit, community health initiativesPublic health departments, hospitals, research firms
Common Search & ComparisonOften compared for entry-level or volunteer rolesCompared for professional, paid roles in public health data analysis

Volunteering Public Health Data Science typically involves unpaid work focused on community projects and requires minimal formal credentials. In contrast, Public Health Data Analysts are paid professionals with relevant degrees working in formal organizations. Both roles utilize data skills but differ mainly in setting, compensation, and credential requirements.

What is volunteering in public health data science?

Volunteering in public health data science involves offering your time and skills to help collect, analyze, and interpret health-related data for organizations or communities, usually without compensation. Volunteers in this field support projects like tracking disease outbreaks, evaluating health programs, or improving data systems. Their work helps organizations make informed decisions that improve public health outcomes. This role is ideal for those with an interest in data science and a passion for public health, and it can provide valuable experience for future careers.
More about Volunteering Public Health Data Science jobs
What cities are hiring for Volunteering Public Health Data Science jobs? Cities with the most Volunteering Public Health Data Science job openings:
What states have the most Volunteering Public Health Data Science jobs? States with the most job openings for Volunteering Public Health Data Science jobs include:
What job categories do people searching Volunteering Public Health Data Science jobs look for? The top searched job categories for Volunteering Public Health Data Science jobs are:
Infographic showing various Volunteering Public Health Data Science job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Associate Research Scientist in Biostatistics, Data Science Data Equity

Associate Research Scientist in Biostatistics, Data Science Data Equity

Yale University

New Haven, CT • On-site

$59K - $59K/yr

Full-time

Posted 29 days ago


Yale University rating

8.6

Company rating: 8.6 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

67th of 612 rated colleges and universities


Job description

Description
We are actively recruiting an Associate Research Scientist as part of the new schoolwide Public Health Data Science and Data Equity Initiative, with a primary appointment in the Department of Biostatistics.
The Associate Research Scientist will work with Dr. Bhramar Mukherjee, Ph.D, the inaugural Senior Associate Dean of Public Health Data Science and Data Equity, Anna M.R. Lauder endowed Professor of Biostatistics and Professor of Chronic Disease Epidemiology. The research involved will focus on analysis of electronic health records linked to biobanks, real-world healthcare data. There may also be opportunities for collaboration with faculty with experience in cancer and cardiovascular diseases. Involvement in training and mentoring and helping to organize an undergraduate summer program in biostatistics and data science will be an integral part of the position. The position is for a one-year term that is renewable based on availability of resources, satisfactory performance and progress.
Responsibilities include:
• Providing expert biostatistical/computational consultation and collaboration on study design, implementation, analysis and the preparation of protocols, grants, and manuscripts for projects related to real world healthcare data as part of the Public Health Data Science and Data Equity Initiative
• Coding and visualization in R/Python
• Planning, conducting and overseeing comprehensive statistical analysis of biobank data
• Creating digital ecosystems that enables external linkage and harmonization across global biobanks
• Publishing and presenting research results in peer-reviewed professional journals and at scientific conferences.
• Developing tools and processes that enable seamless integration and analysis of multiple biobanks by community researchers
• Helping with programs and educational initiatives related to public health data science
• Engage in novel biostatistical research related to electronic health records, selection bias, missing data, causal inference and machine learning
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
Organization: Yale School of Public Health
Department: Biostatistics
Primary Location: New Haven, CT
Education Level: PhD
Shift: Days, 40 hours/week
Expected Start Date: As early as May 1, 2025
Qualifications
Qualifications:
• Completed doctorate in Biostatistics, Statistics, Data Science, Computer Science or a related field.
• Demonstrated track record of research and publication.
• Excellent oral and written communication skills and the ability to work effectively with a wide range of constituencies in a diverse interdisciplinary team.
• Proficiency with statistical computing (e.g., R, Python or C/C++).
• Interest and expertise in large-scale data management, linkage and data integration.
• Demonstrated capacity to work both collaboratively and independently.
• Ability to handle complex topics and explain them well to practitioners and non-quantitative audience.
• Strong strategic, analytical, and problem-solving skills.
• Strong interpersonal, project leadership, and management skills to facilitate timely and professional deliverables.
• Previous mentoring and teaching experiences are desirable but not required.
• A minimum of 2-5 years of experience in a research statistician, collaborative quantitative data scientist role is preferred.
Application Instructions
To apply:
Applicants are asked to submit a (1) CV, (2) cover letter that addresses their specific interest in this position, (3) statement of research/professional accomplishments/interests and (4) the names and contact information for three professional references via Interfolio. Review of applications will begin immediately and will continue until the position is filled.
Questions regarding this position should be directed to: matthew.schlager@yale.edu

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