Stanford University School of Medicine and the Heart Center Clinical and Translational Research Program (CTRP) are seeking a Research Data Analyst 2 to extract, compile, harmonize, analyze, and visualize complex clinical and operational data for pediatric cardiology patients.
Requirements
- SQL, Python, R, or other appropriate languages
- Analysis of longitudinal data
- Programming and query languages including Sql, R and Python
- Database management
- Domain knowledge (national cardiac registries) of PAR and single ventricle physiology datasets.
- Working UNIX/Linux environment.
- Cloud-based computing platforms such as Google Cloud Platform.
Responsibilities
- Extract clinical and operational data from internal data repositories into usable formats and develop pipeline for ongoing data extraction with new data generation, using SQL, Python, R, or other appropriate languages.
- Compile survey data and clinical research data into usable formats.
- Obtain and harmonize external data with local data, including activities such as converting among data storage formats, merging based on common identifiers, excluding irrelevant data, consolidating naming and labeling strategies, and generating analysis-ready datasets.
- Analyze large, multi-dimensional and longitudinal data sets including Cox regression and multivariable modeling, employing prediction modeling or hypothesis testing approaches as appropriate.
- Design and implement tools to independently interpret, analyze and visualize complex data from PAR and single ventricle physiology patients, including clinical, registry, operational, and survey data (including national data registries).
- Devise and implement data quality checks to ensure data are clean, accurate, and ready for analysis.
- Refine data pipelines as needed to minimize inaccurate or incomplete data. This includes utilizing Google Cloud platform tools to manage and analyze data.
Other
- May telecommute within area of intended employment at employerâs discretion.
- Masterâs in bioinformatics, Biology, Public Health, Biostatistics or a related field and three yearsâ experience as a data analyst, research data analyst or occupation in bio-informatician or in biostatistics. Or, Bachelorâs in Bioinformatics, Biology, Public Health, Biostatistics, or a related field and five yearsâ experience as a data analyst, research data analyst or occupation in bio-informatician or in biostatistics.
- Mentoring staff in data analysis and data management.
- Preparing complex research data, performing advanced statistical analysis including Cox regression and multivariable modeling for journal publications and presentations.
- Full-time
