Stanford University School of Medicine and the Heart Center Clinical and Translational Research Program (CTRP) are seeking a Research Data Analyst 2 to manage and analyze large-scale longitudinal data sets derived from clinical, operational, registry, and survey data. Work under supervision of the principal investigator and/or clinical research manager.
Duties include:
·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.
·Identify relevant publicly available datasets and registries, from the National Institutes of Health, multi-institutional collaboratives, and various other sources.
·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.
·Conduct feature engineering and missing data imputation as needed, and conduct reliability and validity checks.
·Restructure datasets for analyses conducted independently and with other quantitative investigators as needed.
·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).
·Identify currently unavailable data elements from available data sets, develop strategies for obtaining necessary data, and prioritize data collection approaches based on needs of division stakeholders.
·Maintain comprehensive records of available and obtainable datasets, including data elements, dates, numbers of observations, etc. (this includes developing dashboards for data visualization, geared towards pediatric cardiology patients).
·Oversee and maintain access to data resources, ensuring compliance with all local and external regulatory and privacy requirements, including the IRB, funding agencies, and database guidelines.
·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.
·Serve as the technical expert for the Division of Pediatric Cardiology for all new statistical design.
·Directly manage and mentor team members in data quality and management.
* - Other duties may also be assigned
~ All members of the Department of Pediatrics are engaged in continuous learning and improvement to foster a culture where diversity, equity, inclusion, and justice are central to all aspects of our work. The Department collectively and publicly commits to continuously promoting anti-racism and equity through its policies, programs, and practices at all levels. ~
Stanford University provides pay ranges representing its good faith estimate of what the University reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location, and external market pay for comparable jobs. The pay range for this position working in the California Bay area is $104,358.00 - $128,038.00 annually.
DESIRED QUALIFICATIONS:
Bachelor’s, MS or PhD in Bioinformatics, Biology or a related field with at least three years of relevant experience
Strong background in bioinformatics, including the analysis of longitudinal data
Bioinformatics, including the analysis of longitudinal data, utilizing programming and query languages including Sql, R and Python, database management.
Domain knowledge (national cardiac registries) of PAR and single ventricle physiology datasets.
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.
Working UNIX/Linux environment.
Cloud-based computing platforms such as Google Cloud Platform.
Developing and maintaining live dashboards and complex data visualizations specifically tailored for monitoring and improving outcomes in pediatric cardiology.
EDUCATION & EXPERIENCE (REQUIRED):
Master’s in Bioinformatics, Biology, Public Health, Biostatistics or a related field and three years’ experience as a data analyst, research data analyst or occupation in bio-informatician or in biostatistics. Or, Bachelor’s in Bioinformatics, Biology, Public Health, Biostatistics, or a related field and five years’ experience as a data analyst, research data analyst or occupation in bio-informatician or in biostatistics.
KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):
·Bioinformatics, including the analysis of longitudinal data, utilizing programming and query languages including Sql, R and Python, database management.
·Domain knowledge (national cardiac registries) of PAR and single ventricle physiology datasets.
·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.
·Working UNIX/Linux environment.
·Cloud-based computing platforms such as Google Cloud Platform.
·Developing and maintaining live dashboards and complex data visualizations specifically tailored for monitoring and improving outcomes in pediatric cardiology.
CERTIFICATIONS & LICENSES:
None
WORKING CONDITIONS:
Some work may be performed in a laboratory or field setting.
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