Description

Position Title: Data Programmer

Position posting date: 06/09/2022

Position start date: ASAP or until filled 

Salary/Range: Dependent on Experience (DOE)

Status: Full time (40 hours/wk), benefits eligible

Work Schedule: Monday – Friday, 8:00am to 4:30pm

Service/Division: Research/Gastroenterology

Work Location: VMRF

Job Code: SG 1261

The Data Programmer will work with a diverse group of clinicians, statisticians and epidemiologists focused on advancing research in cancer detection and prevention. Responsibilities include designing and managing databases of a large, retrospective study on colon cancer surveillance and providing technical support for installation, configuration and maintenance of systems. Creates and maintains data systems that will support several retrospective studies on various types of cancer. Designs, develops and maintains web-based Electronic Data Capture systems, such as REDCap. Develops training documents and implements database collection process, including but not limited to quality control and data integrity. Maintains documentation such as SQL queries activities and provides feedback to the team. Designs, maintains and optimizes datasets (predominantly SQL and SAS) for use in statistical analysis. Generates, reviews and analyzes data reports in order to analyzes accuracy, deliverables, and study design. Organizes, cleans, and codes data and executes data analyses. Contributes to the analysis and interpretation of data. Complies with safety and security policies and procedures. Reports potential unsafe conditions. Works well with others. May perform additional duties as required.

Requirements

Bachelor’s degree (BA/BS) in a related field (preferably Computer Science or Information Technology) from an accredited college or university AND at least 1 year of related experience; or an equivalent combination of education and experience. Experience with data programming (e.g. performing data queries with SQL) and data management (e.g. RedCap) required. Experience with data analysis software (e.g. SAS or R) is preferred.