Research Associate/Statistician
The Choi Lab in the Department of Oral Health Policy and Epidemiology (OHPE) seeks a research associate to join our team and provide quantitative and analytical support for research projects evaluating the impact of health policies and healthcare delivery models on health outcomes and health disparities.
Our research uses large-scale administrative claims, electronic health records, national survey data, and simulation modeling approaches to generate evidence that informs health policy and promotes equitable health outcomes.
The selected candidate will work closely with a multidisciplinary team, including clinicians, statisticians, decision scientists, and health services researchers. The individual will contribute to all phases of the research process, including study design, data management, statistical analysis, interpretation of findings, manuscript preparation, and grant development. This position is ideal for an individual who enjoys solving complex data problems, critically evaluating analytic approaches, and contributing intellectually to scientific research.
Responsibilities
• Collaborate on study design, development of analytic plans, statistical analyses, interpretation of results, and preparation of manuscripts and scientific reports.
• Manage, clean, validate, and analyze large healthcare datasets, including electronic health records, administrative claims, and national survey data.
• Develop reproducible workflows for data processing, quality control, statistical analysis, and documentation.
• Critically evaluate data quality, analytic assumptions, and unexpected findings; conduct sensitivity analyses and propose solutions to methodological challenges.
• Participate in the development and implementation of population-level simulation models to evaluate the clinical, economic, and equity impacts of health policy interventions.
• Support preparing and drafting research protocols through literature reviews and eliciting required data elements.
• Work independently to identify and troubleshoot analytical issues, communicate methodological decisions and findings clearly to the research team, and contribute to discussions regarding interpretation and next steps.
This is an annual term position reviewed each academic year on or before June 30th, with the possibility of extension, contingent upon work performance, business need, and continued funding to support the position.
Basic Qualifications
• Bachelor’s degree in statistics, biostatistics, epidemiology, data science, computer science, or a closely related field with 2+ years of relevant experience.
• Proficiency in statistical programming languages (R, SQL or Python) is required.
Additional Qualifications
• Master’s degree preferred. Prior experience with causal inference methods, simulation modeling, machine learning, or analysis of large healthcare datasets is strongly preferred.
Special Instructions
• Interested applicants should submit a cover letter, their curriculum vitae, and names of three references.
• Work is performed in an office setting. Individual flexible and remote work options for this role will be discussed during the interview process.
Salary Range: $65,000-$95,000. Compensation for the selected candidate will be determined by several factors, including years of experience, relevant training or qualifications, area of education/training/scholarship, and professional achievements.
EEO/Non-Discrimination Commitment Statement
Harvard 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 differences help our community advance Harvard’s academic purposes. Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university’s non-discrimination policy.
Harvard’s equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.
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Our research uses large-scale administrative claims, electronic health records, national survey data, and simulation modeling approaches to generate evidence that informs health policy and promotes equitable health outcomes.
The selected candidate will work closely with a multidisciplinary team, including clinicians, statisticians, decision scientists, and health services researchers. The individual will contribute to all phases of the research process, including study design, data management, statistical analysis, interpretation of findings, manuscript preparation, and grant development. This position is ideal for an individual who enjoys solving complex data problems, critically evaluating analytic approaches, and contributing intellectually to scientific research.
Responsibilities
• Collaborate on study design, development of analytic plans, statistical analyses, interpretation of results, and preparation of manuscripts and scientific reports.
• Manage, clean, validate, and analyze large healthcare datasets, including electronic health records, administrative claims, and national survey data.
• Develop reproducible workflows for data processing, quality control, statistical analysis, and documentation.
• Critically evaluate data quality, analytic assumptions, and unexpected findings; conduct sensitivity analyses and propose solutions to methodological challenges.
• Participate in the development and implementation of population-level simulation models to evaluate the clinical, economic, and equity impacts of health policy interventions.
• Support preparing and drafting research protocols through literature reviews and eliciting required data elements.
• Work independently to identify and troubleshoot analytical issues, communicate methodological decisions and findings clearly to the research team, and contribute to discussions regarding interpretation and next steps.
This is an annual term position reviewed each academic year on or before June 30th, with the possibility of extension, contingent upon work performance, business need, and continued funding to support the position.
Basic Qualifications
• Bachelor’s degree in statistics, biostatistics, epidemiology, data science, computer science, or a closely related field with 2+ years of relevant experience.
• Proficiency in statistical programming languages (R, SQL or Python) is required.
Additional Qualifications
• Master’s degree preferred. Prior experience with causal inference methods, simulation modeling, machine learning, or analysis of large healthcare datasets is strongly preferred.
Special Instructions
• Interested applicants should submit a cover letter, their curriculum vitae, and names of three references.
• Work is performed in an office setting. Individual flexible and remote work options for this role will be discussed during the interview process.
Salary Range: $65,000-$95,000. Compensation for the selected candidate will be determined by several factors, including years of experience, relevant training or qualifications, area of education/training/scholarship, and professional achievements.
EEO/Non-Discrimination Commitment Statement
Harvard 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 differences help our community advance Harvard’s academic purposes. Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university’s non-discrimination policy.
Harvard’s equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.
#J-18808-Ljbffr