Data Manager (Full-Time)

Job Summary The NYU Program of Nutrition at Steinhardt, the Center of Advancement and Dissemination of Intervention Optimization (cadio) at the NYU Global School of Public Health, and the Institute of Human Development and Social Change (IHDSC) are seeking a Data Manager to support Dr. Angela Trude and Dr. Jillian Strayhorn and the OPT-FRESH research team. This role will play a central role in supporting all aspects of the project's data activities, including developing and maintaining data systems, ensuring compliance with NIH Data Management and Sharing (DMS) requirements, and supporting data collection, quality assurance, and documentation. Project Overview OPT-FRESH is a 5-year NIH-funded intervention trial addressing gaps in healthy food access among low-income families. Using the multiphase optimization strategy (MOST), the study tests three intervention components designed to reduce barriers to online healthy food purchases: 1) weekly text messages to improve trust in online grocery services; 2) weekly match of up to $10 as a financial inventive for purchasing FVL online; and 3) weekly instant shoppable grocery lists of tailored meal suggestions using SNAP-Ed recipes. OPT-FRESH will provide a unique opportunity to identify effective, scalable, and efficient strategies that could be used to reach the over 44 million people in the U.S., including six million children, experiencing food insecurity, thus addressing important social determinants of health that explain health disparities related to cardiovascular disease. Specific Responsibilities Develop and maintain secure data management systems for the project. Implement protocols for data collection, entry, storage, quality assurance, and security. Support study staff and research assistants in data collection and processing activities. Oversee data cleaning, merging, and preparation for analysis. Ensure compliance with NIH Data Management and Sharing policies, including preparation of metadata, codebooks, and documentation. Work closely with the PI, postdoctoral fellow, and analysts to facilitate data use for manuscripts, presentations, and grant reporting. Assist with the preparation of data sets for sharing with external collaborators and public repositories. Maintain detailed records of all data-related activities and decisions. Provide training and support to research staff and students on data handling procedures. Contribute to dissemination efforts through tables, figures, and descriptive analyses for reports, presentations, and publications. Working Conditions In-person: meetings and data analysis activities will be conducted in the NYU Washington Square Campus, where the Data Manager will have a designated work-desk, filing cabinets, and computer. Time Frame One-year position with potential renewal for up to five years. In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is $60,000-$70,000. New York University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer. Per NYU's remote-work policy, this position is expected to be completely in-person. This position will not have direct supervisory responsibilities. Qualifications and Competencies Master's degree in Public Health, Epidemiology, Biostatistics, Data Science, or a related field; PhD preferred. Demonstrated experience in managing large or complex datasets, preferably in public health, nutrition, or social science research. Proficiency with data management and analysis tools (e.g., REDCap, Qualtrics, STATA, SAS, R, or Python). Familiarity with NIH Data Management and Sharing requirements and best practices. Strong organizational skills and attention to detail. Ability to work collaboratively with a multidisciplinary team. Excellent communication skills and ability to prepare clear documentation. Experience with randomized controlled trials preferred. The position will begin October 1, 2025 . Qualified candidates should submit a one-page cover letter, a sample of data analysis materials (e.g., codebooks, syntax, summary report) and the names, phone numbers, and email addresses of three references via Interfolio. 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