Research Assistant II Non-Lab
Listed on 2026-02-04
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Research/Development
Public Health, Data Scientist, Research Scientist, Clinical Research -
Healthcare
Public Health, Data Scientist, Clinical Research
Overview
Harvard T.H. Chan School of Public Health — Department of Health Policy and Management is a research center focused on producing actionable evidence to promote quality, equity, and resilience across health care delivery systems. HQO brings together a multidisciplinary team to evaluate and inform health reform efforts. This is a term appointment position with potential for extension.
Job SummaryThe Healthcare Quality and Outcomes Lab (HQO) at the Harvard T.H. Chan School of Public Health is a research center that uses large national datasets to evaluate the effectiveness and unintended consequences of US health reform. HQO faculty seek an energetic and organized individual to assist with a portfolio of multidisciplinary health policy and health services research projects, with opportunities for mentorship and professional growth.
Responsibilities- Preparation of scientific manuscripts and presentations, with opportunities for co-authorship
- Performing literature reviews and managing references
- Assistance with grant-writing and research proposals
- Coordination of project communications, research meeting coordination and documentation
- Producing charts and tables for manuscripts and presentations
- Writing policy briefs, op-eds, press releases, and other products
- Compiling and cleaning data sources
- Statistical programming and analysis
- Website maintenance (e.g., updating HQO website to feature new publications)
- Other duties as assigned
Basic Qualifications:
- 2+ years of related work experience; a combination of education and experience may be considered
Additional
Qualifications and Skills:
- Bachelor's Degree in health sciences, social sciences, or statistics
- Demonstrated knowledge of health policy and health services research
- Experience with healthcare-related topics such as health policy or health services research or related coursework
- Strong writing background
- Experience with reference management software
- Experience with statistical analysis and data science (running and interpreting regressions, data visualization)
- Experience in quantitative research methods and analysis
- Experience with Microsoft Word, Excel, and Power Point
- Experience with SAS, Stata, or R is a plus
- Strong organizational skills and attention to detail
- Excellent communication skills
- Appointment End Date: One year from date of hire
- Standard Hours/
Schedule:
35 hours per week - Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position
- Pre-Employment Screening: Identity
Harvard offers a comprehensive benefits package designed to support work-life balance and wellbeing, including medical, dental, vision coverage, retirement plans, wellbeing resources, family support, professional development, and commuter benefits. Details are available on the Benefits & Wellbeing page.
EEO/Non-Discrimination CommitmentHarvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our equal employment opportunity policy prohibits discrimination on protected characteristics.
Work Format DetailsThis position may be performed at a non-Harvard location. The work schedule and location will be set by the department. When not at a Harvard location, employees must work in a Harvard registered state in compliance with the university’s Employment Outside of Massachusetts policy. Certain visa types and funding sources may limit work location.
Salary GradeThis position is salary grade level 053. See Harvard salary ranges for details.
Legal and ComplianceHarvard does not sponsor visas for staff positions. Pre-employment reference checks and background screenings are required. The O/R period may be waived for internal transfers. The health of our workforce is a priority; vaccination recommendations are encouraged.
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