How to Apply:
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The Breast Cancer Surveillance Data Manager of the San Francisco Mammography registry is responsible for data coding and mapping of questionnaires regarding radiology, biopsy, cancer and vital statistics information from mammography facilities in the San Francisco Bay Area. The individual should have a strong ability to manipulate data using SAS, map clinical data to defined variables in the Breast Cancer Surveillance Consortium (BCSC) Data Dictionary, as well as recognize and problem solve data issues and perform statistical analysis including frequencies and cross tabulations.
Responsibilities:
This Data Manager should also have knowledge of quality control procedures. The Breast Cancer Surveillance Data Manager is the professional who applies acquired job skills, policies, and procedures to complete substantive assignments, projects, and tasks of moderate scope and complexity; exercises judgment within defined guidelines and practices to determine appropriate action.
The Breast Cancer Surveillance Data Manager uses professional bioinformatics concepts. Applies computational procedures to resolve a variety of analysis and research issues. Works on assignments of moderate scope where analysis of data requires a review of a variety of factors. Assists in additional analyses as needed to achieve research objectives. Uses knowledge of breast cancer to problem solve data issues, create data sets for ancillary studies, and perform simple analyses.
Skills / Education Requirements:
Required Qualifications:
- BS degree in Computer Science, Statistics, Operational Research or other degree with emphasis on data management, or an equivalent combination of education / experience.
- Five years full-time database management and SAS programming experience, including advanced data step programming (Base SAS), SAS macro language, Proc SQL and SAS / ACCESS.
- Advanced skills in SAS with experience manipulating very large databases (millions of observations and hundreds of variables).
- Understanding of database design and data elements in the BCSC data dictionary is essential to be able to map acquired data from various clinical data systems. Quality control and understanding of how data will be used to address research questions is important to mapping data to the SFMR database and providing data to ancillary studies.
- Thorough understanding of efficient database design and structure concepts and expertise in working with data in a variety of formats (e.g. SAS, dbf, FileMaker Pro, Access, XML, Excel, Salesforce).
- Excellent organization, documentation and communication skills.