This is a grant funded position and is not eligible for severance pay.
The Jean Mayer USDA Human Nutrition Research Center on Aging (HNRCA) is one of six USDA human research centers created by Congress to study the effects of human nutrition on health. The HNRCA is the site for conducting some of the most advanced research in the world on the relationship between nutrition and the aging process. The Biostatistics and Data Management Core is one of the HNRCA core service units. The core unit consults and assists in study design, implementation, and data analysis/management and develops new statistical techniques and software to support HNRCA research activities. Scientists confer with the unit in the early stages of a study to discuss project goals, available resources, accepted statistical, bioinformatics and data management practices, and the appropriate response variables and covariates for proper statistical analysis.
The Dietary Assessment Unit (DAU) at the HNRCA is a scientific core unit that provides dietary assessment services within the HNRCA as well as in collaboration with Tufts and outside institutions. The DAU provides expertise and services in dietary data collection methods, coding, data cleaning and management and dietary data analysis for projects ranging from small HNRCA intervention studies to larger multidisciplinary protocols to existing dietary data sets. The unit assists in the development of dietary intervention sections of new protocols, advises on dietary data collection methodology, develops necessary manuals of procedures and nutrition-related materials and works to create new methodology to improve the collection of dietary data. The DAU provides a centralized, consistent and high standard dietary data collection service across the HNRCA.
The major responsibilities of this position include support for the Dietary Assessment Core Unit with data cleaning, data manipulation and the management of dietary data output from programs such as NDSR (nutritional analysis software) and various FFQs and brief dietary data methods. Maintain and develop SAS programs for quality assurance processes, quality control checks, and the coding of various nutrition and dietary pattern scores. Additional responsibilities will include guiding the adoption of best practices for data collection, curation and archival across core units and scientific laboratories as well as working with relational databases and the integration of multidimensional clinical datasets for analysis.
- Bachelor’s degree in health sciences or related field and at least two years’ experience in data management and SAS programming
- Experience working with SAS macros
- Strong data management skills, including the ability to handle and organize data from different sources and to perform quality control processes
- Working knowledge of Good Clinical Practices, good Manufacturing Practices, Clinical research, Clinical trial process and related regulatory requirements and terminology
- Strong verbal and written skills, good organizational, interpersonal, and team skills
- Demonstrated proficiency in English language skills (reading, writing, and speaking)
- Proficient in Microsoft Office, including Excel and Access
- Master’s degree in statistics or health sciences-related field and 2-3 years’ experience in a research setting
- Intermediate programming and analysis experience using SAS, R, Microsoft Excel, Microsoft Access and relational databases for data management and quality control
- Working knowledge of relational databases
- Strong time management and ability to handle multiple projects, organize work, and set priorities to meet deadlines while working within prescribed time constraints
- Confidentiality and discretion are essential
- Demonstrated professional and ethical manner at all times
Special Work Schedule Requirements:
This position may occasionally require to work on nights and/or weekends as determined by need
An employee in this position must complete all appropriate background checks at the time of hire, promotion, or transfer.
Equal Opportunity Employer – minority/females/veterans/disability/sexual orientation/gender identity.
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