Position Description

The Research Assistant will support Professor Nicole Maestas, an economist in the Department of Health Care Policy at Harvard Medical School, on daily operations of research projects in the fields of health and labor economics, including topics on disability insurance, work capacity and employment, health insurance and health care utilization, and disparities in access to mental health care.
The most important task of the Research Assistant will be to use statistical software to work with large data sets, including possibly health insurance claims datasets. This work will involve the cleaning and development of data files as well as using econometric and statical analysis to analyze the data. A background in statistical programming (STATA and/or R preferred) and a basic understanding of economics/econometrics is strongly encouraged.
The Research Assistant is expected to have strong critical thinking and excellent writing skills to assist with drafting of manuscripts, presentations, and grant proposals. The Research Assistant will also participate in team meetings, conduct literature reviews, and assist with IRB, data use applications, and progress reports. This position is ideal for candidates with an interest in economics and/or health policy and who have plans for future doctoral studies. This is a one-year grant-funded position, with possibility for renewal.
In your cover letter, please address the following:

• Your interest in this position.
• Your familiarity with programming languages (e.g., STATA, R, SAS, SQL, etc.).
• Your prior experience as a research assistant and/or independent research projects (e.g., a thesis); please describe quantitative analysis tasks you performed.

Basic Qualifications

• Two or more years of related research experience. Higher education may count towards years of experience.
• Applicant should have proficiency in using statistical software packages such as STATA and/or R.

Additional Qualifications and Skills

• BA or BS in economics, statistics, public policy with a quantitative focus, or related field.
• Must demonstrate interest, experience, or background in the areas of disability, labor, health policy and/or aging.
• Must be proficient with standard computer software such as Word, Excel, and PowerPoint.
• Proficiency in LaTeX encouraged.
• Must be willing to learn other software as needed (e.g., SAS, R).
• Independent judgment, patience, and excellent communication skills are required to respond efficiently to varied/complex tasks.
• Organization and attention to detail is a must.
• Flexibility and the ability to work with a team are essential.
• Must be able to maintain a calm and cooperative attitude during periods of increased activity.

Additional Information

This is a one-year term position from the date of hire, with the possibility of extension, contingent upon work performance and continued funding to support the position. 
The health of our workforce is a priority for Harvard University. With that in mind, we strongly encourage all employees to be up-to-date on CDC-recommended vaccines.
Please note that we are currently conducting a majority of interviews and onboarding remotely and virtually. We appreciate your understanding.
The Harvard Medical School is not able to provide visa sponsorship for this position.
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Commitment to Equity, Diversity, Inclusion, and Belonging

We are committed to cultivating an inclusive workplace culture of faculty, staff, and students with diverse backgrounds, styles, abilities, and motivations. We appreciate and leverage the capabilities, insights, and ideas of all individuals. Harvard Medical School Mission and Community Values
https://hms.harvard.edu/about-hms/campus-culture/mission-community-values-diversity-statement

EEO Statement

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions, or any other characteristic protected by law.