Research Data Analyst I
University Of California San Francisco Foundation
San Francisco, CA · Posted October 27, 2026
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How AI is used in this kind of work
Among social science research assistants, AI is already used for a large share of the tasks. Measured exposure for social science research assistants: 44% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
Job Function Summary
Involves gathering and analyzing a wide variety of research data. Designs and conducts research including selecting data samples and analyzing collected information according to established statistical methods. Prepares reports, charts, tables, and other visual aids to interpret and communicate data and results.
Generic Scope
With support, gather and analyzes data and develops reports, charts and tables as appropriate. Functions with guidance and supervision.
Custom Scope
Applies knowledge as a research professional with an understanding of statistical and / or other analysis techniques designed to support research projects, with guidance.
Department Overview
The Nephrology Division spans multiple campuses with faculty and staff located at the UCSF Health, San Francisco Veterans Affairs Medical Center, and Zuckerberg San Francisco General. The Nephrology Division consists of faculty, fellows, and staff whose work is grounded in deep commitment to and respect for patients with kidney disease.
The Nephrology Division has employed and trained leaders in academic nephrology, superb clinical research scientists and basic scientists, and outstanding clinical nephrologists. Our faculty are leading experts in adult nephrology: including acute kidney injury, chronic kidney disease, hypertension, electrolyte disorders, and kidney transplantation.
Our mission continues in this tradition: expanding the frontiers of basic and clinical investigation in nephrology, training the next generation of academic nephrology leaders and providing the highest level of patient care. Our division within and the UCSF School of Medicine overall provides a premier academic environment for faculty and trainees to provide outstanding clinical care and to be at forefront of kidney research worldwide.
Statistical and Data Analysis
Under direct supervision, performs basic statistical and data analysis, compiles research data. Contributes to analysis of data.
Normalize and create a common data format from multiple, disparate databases.
Write code to automatically and quickly evaluate and optimize the accuracies of different statistical models.
Implement data cleaning and modeling given a study design, imputing missing variables, and using Fine-Gray, Cox, logistical, and other models.
Research Data Collection and Preparation
Collect research data and prepares it for analysis.
Prepare data collected in NIH-funded clinical trials and cohort studies to fulfill Data Management and Sharing (DMS) Plan requirements.
Research Data Quality and Testing
Supports testing of research instruments and data sources.
Run data quality checks, develop and implement data cleaning, merging rules.
Required Qualifications
Acquiring knowledge of research function.
Aquiring statistical analysis, database management and systems programming.
Ability to communicate complex information in a clear and concise manner both verbally and in writing.
Analyze complex information requirements and documents them using formal data definition techniques and naming standards. Gathers, analyzes, prepares and summarizes information from subject matter experts and technical personnel.
Familiarity with data quality and governance issues and requirements.
Acquiring knowledge of data management systems, practices and standards.
Acquiring knowledge of relevant rules and regulations.
Self-motivated and works independently and as part of a team.
Demonstrated strong problem-solving skills. Able to learn effectively and meet deadlines.
Strong organizational skills.
Critical thinking skills and attention to detail.
Knowledge of statistics and machine learning.
Ability to program in SAS, STATA, or equivalent (e.g. R).
Required Education
Bachelor’s degree in data science or related field (with completion of first-author original investigation clinical research manuscript demonstrating proficiency with data manipulation and data analysis) and / or equivalent experience / training.
Preferred Certifications
Collaborative Institutional Training Initiative (CITI) training.
HIPPA training.
Licenses
None listed.