The CUNY ISPH has a rapidly growing research portfolio focused on respiratory infection, mental health, and population health interventions. We are recruiting for a data analyst to support Project PROTECTS, a study focused on understanding and improving respiratory infection outcomes using longitudinal cohort data.

Data collection for Project PROTECTS will be largely complete by June 2026. As such, this is a time-limited, high-impact analytic role focused on rapidly executing analyses and producing peer-reviewed manuscripts. The analyst will play a central role in translating a rich, longitudinal dataset into publications and will be expected to operate with a high degree of independence in a fast-paced, output-driven environment.

The position comes with a one year hire commitment, with the possibility of extension and/or transition to other projects within the portfolio based on performance and funding availability. This can be a remote position, as long as the employee can work EST hours and is already authorized to work in the United States without sponsorship.

Job Duties
• Quickly become familiar with PROTECTS study design, cohort structure, and analytic priorities
• Manage, clean, and prepare complex datasets for analysis, ensuring analytic readiness and reproducibility
• Independently conduct advanced epidemiologic analyses, with a focus on longitudinal and repeated-measures data
• Rapidly lead analyses, draft, and publish papers in peer-reviewed journals
• Apply appropriate statistical methods (e.g., mixed effects models, longitudinal regression approaches, causal inference methods as appropriate)
• Review the work of other analysts, advising on statistical methods and protocol where necessary
• Support analyses and manuscripts being led by other members of the investigative teams
• Develop and maintain analytic code in SAS (and/or R), including the ability to review and troubleshoot code across team members
• Translate analytic findings into clear, concise written outputs for manuscripts and reports
• Contribute to future grant applications and follow-on projects, as applicable and interested

Required
• MPH in epidemiology (or related field) with strong training in epidemiologic and biostatistical methods
• Strong demonstrated experience with longitudinal data analysis is required
• 2–4 years of experience in an epidemiologic data analyst role or doctoral-level training with substantial applied longitudinal analytic experience
• Demonstrated ability to lead or substantially contribute to peer-reviewed manuscripts (writing is a core function of this role)
• Ability to review code in SAS (fine to primarily operate and code in R, but must be able to review or use SAS code)
• Ability to efficiently prioritize and execute projects independently and under tight timelines
• Excellent written and verbal communication skills
• Team player with strong collaborative instincts

Additional Considerations (Highly Valued)
• Advanced training in epidemiology or biostatistics (e.g., doctoral coursework or degree in progress/completed)
• Experience applying longitudinal or causal inference methods to real-world public health data
• Prior experience working with cohort studies, intervention studies, or mental health data
• Experience working in fast-paced, publication-driven research environments