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.

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.

• 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.

• Master’s degree preferred. Prior experience with causal inference methods, simulation modeling, machine learning, or analysis of large healthcare datasets is strongly preferred.

• 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.

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