Division of Pulmonary (ZSFG)

Full Time

77979BR

Job Summary

This Research Analyst will have significant experience in selecting and applying appropriate statistical methods to analyze complex spatially distributed environment, structural, and social data in ongoing and de novo studies of respiratory health in diverse populations. This position requires strong analytic, problem solving, and programming skills to analyze and interpret very large data sets with a variety of variable types. The incumbent will also co-lead with the investigator the selection of new data instruments based on the published literature and set up and design the data collection and sampling strategies for new studies; design, plan, and execute statistical analysis; perform complex data analysis (including but not limited to case cross over, time-series, hierarchical/multi-level modeling, mediation analysis); and contribute to the accurate interpretation of results. The individual will work with the scientific team on multiple research projects, and will summarize results for presentation. They will provide support for manuscript preparation. The incumbent's role in analysis and manuscript preparation will be acknowledged with authorship according to her or his effort.

The incumbent will have an integral role in data management, including data cleaning, report preparation, data dictionary creation, database QA, and software/hardware maintenance and backups.

The incumbent will work closely with other members of the Pulmonary Division and Program for Clinical Research and be a resource, including providing statistical mentorship. The main role of the incumbent will be to support post-doctoral fellows and junior faculty in the Division of Pulmonary and Critical Care Medicine. As such, the incumbent will be working on varied projects. The data analyst will work closely with senior faculty to assist in prioritization of projects and to troubleshoot projects. Strong communication skills to a variety of audiences and time management skills are necessary in addition to the statistical, programming, and organizational skills.

The final salary and offer components are subject to additional approvals based on UC policy.

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Department Description

The Division of Pulmonary and Critical Care Medicine at UCSF provides comprehensive medical care for the community, develops innovative research aimed at elucidating basic mechanisms of disease, and translates its research activities into both new clinical initiatives and a rich training environment for the next generation of academic physician scientists.

Required Qualifications

• BA/BS with a major in statistics or a related field and three or more years of professional statistical experience; or an equivalent combination of education and experience; and knowledge and abilities essential to the successful performance of the duties assigned to the position.
• Knowledge of several statistical programs including R, Stata, MS Access, and MS Excel is required to ensure the accuracy of study data, produce relevant datasets for analysis, conduct data analysis, and prepare data for publication/presentation.
• Knowledge of medical terminology with a focus on asthma and eczema diagnosis and treatment is needed to work with the many study collaborators.
• Skills in project management.
• Research skills at a level to evaluate alternate solutions and develop recommendations.
• Experience in clinical research, with preference for experience in asthma or eczema research.
• Outstanding communication and organization skills
• Attentive to details and able to keep careful logs of analyses.
• Experience communicating effectively with colleagues from different disciplines and with community groups in order to facilitate research collaborations
• 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.

Preferred Qualifications

• Master's degree in statistics, epidemiology, or a related quantitative field.
• Good working knowledge of biology.
• Proficiency and experience with iMedris, UCSF's online CHR submission and management system.
• Familiarity with UCSF Internet protocols (including standard disclaimer language) is needed to ensure that any required web site operates in compliance with University standards.
• Familiarity with UCSF/HIPPA requirements.

About 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.

Pride Values

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

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.

Organization

Campus

Job Code and Payroll Title

006257 RSCH DATA ANL 3

Job Category

Professional (Non-Clinical), Research and Scientific

Bargaining Unit

99 - Policy-Covered (No Bargaining Unit)

Employee Class

Career

Percentage

100%

Location

Zuckerberg San Francisco General (ZSFG)

Shift

Days

Shift Length

8 Hours

Additional Shift Details

Monday - Friday; 8:00 AM - 5:00 PM