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QUIL Specialist Biostatistician

Application Window

Open date: September 8, 2022

Most recent review date: Friday, Sep 23, 2022 at 11:59pm (Pacific Time)
Applications received after this date will be reviewed by the search committee if the position has not yet been filled.

Final date: Friday, Mar 8, 2024 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

Position description

QUIL Specialist Biostatistician

The Rheumatology Quality and Informatics Lab at the University of California, San Francisco is seeking a Biostatistician in the Academic Specialist job series (with full benefits) to help lead clinical research efforts. The Rheumatology Quality and Informatics Lab (QUIL, http://quil.ucsf.edu) is led by Drs. Gabriela Schmajuk and Jinoos Yazdany focus 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).

The Biostatistician will work independently to design and execute clinical research studies with high-level guidance from faculty PIs. The Biostatistician will join an exceptional team at QUIL, with latitude to lead methodologic research in study design and analysis topics, drawing on QUIL’s extensive past and ongoing research projects. The hybrid position is ideally suited for people with PhD-level training in biostatistics, statistics or epidemiology, but we will consider exceptional candidates with a combination of a master’s degree and relevant experience working on research using real-world data or electronic health data.

Key responsibilities at QUIL will include:
• Use skills as a seasoned, experienced research professional with a full understanding of in-depth statistical analyses and / or research software programming techniques.
• Applies extensive knowledge as a research professional with an in-depth understanding of statistical and/or other analysis techniques designed to support research projects of broad scope and complexity.
• Supervise and support other staff or trainees to execute studies, including verifying data analysis plans and findings.
• Act as the client liaison for our contract with the American College of Rheumatology - working with clients to perform analyses using national patient registry data. These projects last three to six months and involve developing a protocol, executing that protocol, and presenting and sharing results.
• The individual is responsible for conducting data analyses including basic descriptive statistics, comparative analyses, factor analyses, and regression analyses. will also assist in writing scientific manuscripts and help with grant applications as needed.

Appointees in the Specialist series will be expected to engage in specialized research, professional activities and do not have teaching responsibilities. Specialists are expected to use their professional expertise to make scientific and scholarly contributions and may participate in University and Public Service. Screening of applicants will begin immediately and will continue as needed throughout the recruitment period. Salary and rank will be commensurate with the applicants experience and training.

Required Qualifications:
• Master’s degree in biostatistics, statistics, epidemiology or public health plus at least 4 years of related experience.
• Advanced skills associated with statistical analysis, database management and systems programming
• Expertise in SAS, STATA, R or Python statistical packages, Microsoft Word, PowerPoint and Excel
• Experience synthesizing data into presentation format.
• Experience developing study designs.
• Experience writing scientific manuscripts synthesizing research findings.
• In-depth knowledge of research function.
• Advanced ability to communicate complex information in a clear and concise manner both verbally and in writing.
• Advanced ability to think creatively and recommend action steps or strategize solutions relative to research.
• Publication record commensurate with experience, with an emphasis on collaborative contributions.

Preferred Qualifications:
• PhD degree in related area
• Experience conducting research using electronic health record data
• Experience using machine learning techniques
• Experience leading and mentoring small teams (<10) of masters-level statisticians or data scientists

Please apply online at https://aprecruit.ucsf.edu/JPF04151. Applicants’ materials must list current and/or pending qualifications upon submission.

Application Requirements

Document requirements
  • Curriculum Vitae - CV must clearly list current and/or pending qualifications (e.g. board eligibility/certification, medical licensure, etc.).

  • Cover Letter

  • Statement of Research (Optional)

  • Statement of Teaching (Optional)

  • Statement of Contributions to Diversity - Please see the following page for more details: https://diversity.ucsf.edu/contributions-to-diversity-statement
    (Optional)

  • Misc / Additional (Optional)

Reference requirements
  • 3-5 required (contact information only)

Campus Information

As a condition of employment, you will be required to comply with the University of California SARS-CoV-2 (COVID-19) Vaccination Program Policy found here: https://policy.ucop.edu/doc/5000695/SARS-CoV-2_Covid-19.

UC San Francisco seeks candidates whose experience, teaching, research, or community service that has prepared them to contribute to our commitment to diversity and excellence. The University of California 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, disability, age or protected veteran status.

Job location

San Francisco, CA