The Research Data Analyst must have strong quantitative skills and experience working with large data sets and SQL programming. Our research team conducts observational studies using electronic health record data and national patient registry data. The Research Data Analyst will closely work with the Principal Investigator and other project staff. Excellent interpersonal and communication skills are required to efficiently and effectively work with statisticians, co-investigators, research staff, postdoctoral fellows, and graduate students.
The Research Data Analyst will be asked to ensure data quality (assessing data completeness, cleaning, verification, reliability and validity of study variables, and identifying and addressing data gaps and missing data), prepare data for analysis, conduct statistical analysis in support of research proposals and protocols and independently plan studies or supervise lower level analysts in large, complex studies This Data Analyst will assist in preparing the dissemination of findings (e.g. slide presentation, tables, figures, PubMed search), and in submitting IRB approvals and modifications.
The Rheumatology Quality and Informatics Lab (QUIL) at UCSF is led by Drs. Gabriela Schmajuk and Jinoos Yazdany focuses on clinical informatics and health services research in rheumatic disease from a multidisciplinary perspective. Research areas include the evaluation of performance on key rheumatology clinical quality measures, comparative effectiveness and safety of medications used to treat rheumatic conditions, and the use of health information technology that enables health care providers to better manage patient care through secure use and sharing of health information. We were recently named a Data Analytic Center for rheumatology’s national patient registry (called “RISE”) and are building the team that will manage and analyze this new data source (>10 million patient encounters, and growing).
Bachelor’s degree in related area and minimum three years of experience or equivalent combination of experience / training.
Thorough knowledge of research function.
Thorough skills associated with statistical analysis and systems programming.
Thorough skills in analysis and consultation.
Skills to communicate complex information in a clear and concise manner both verbally and in writing.
Skills in project management.
Research skills at a level to evaluate alternate solutions and develop recommendations.
Masters in related field
About University of California San Francisco (UCSF)
The University of California, San Francisco (UCSF) is a leading university dedicated to promoting health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and excellence in patient care. It is the only campus in the 10-campus UC system dedicated exclusively to the health sciences. We bring together the world’s leading experts in nearly every area of health. We are home to five Nobel laureates who have advanced the understanding of cancer, neurodegenerative diseases, aging and stem cells.
UCSF is a diverse community made of people with many skills and talents. We seek candidates whose work experience or community service has prepared them to contribute to our commitment to professionalism, respect, integrity, diversity and excellence – also known as our PRIDE values.
In addition to our PRIDE values, UCSF is committed to equity – both in how we deliver care as well as our workforce. We are committed to building a broadly diverse community, nurturing a culture that is welcoming and supportive, and engaging diverse ideas for the provision of culturally competent education, discovery, and patient care. Additional information about UCSF is available at diversity.ucsf.edu
Join us to find a rewarding career contributing to improving healthcare worldwide.
Equal Employment Opportunity
The University of California San Francisco is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.