Opening for Associate Specialist in Data-Base Driven Health Services Research
Application Window
Open date: November 20, 2024
Next review date: Thursday, Dec 5, 2024 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee.
Final date: Wednesday, May 20, 2026 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
Opening for Associate Specialist in Data-Base Driven Health Services Research
We are recruiting a research specialist to work on projects investigating applied health outcomes, epidemiologic, and economics research with a focus on treatment and medication-related hypotheses to inform health policy.
The appointee will leverage large, real-world databases that includes electronic health records, large population-level surveys, and administrative claims databases to develop and apply statistical approaches for inference on incidence and outcomes.
Required Qualifications:
- Master's degree in a quantitative field (data science, CS, statistics / biostats, math, etc.) or other field or five to ten years of relevant experience.
- Demonstrated experience using statistical packages (eg. R, SAS, Stata).
- Relational database experience with SQL, Python is required.
- The successful candidate will be an independent, highly motivated problem solver who communicates well and enjoys working in a collaborative, interdisciplinary, rapid-paced environment and track record of published research.
- Strong, demonstrated background in one or more of either research, cloud-based data, public health, epidemiology, or statistical or machine learning / AI analytics. Candidate should have the following expertise.
- Leveraged a large-scale healthcare database to conduct and collaborate on multiple research topics
- Worked within data platform to query both standardized and non-standardized electronic health records including patient prescription, hospitalization, lab measurement, and diagnosis data
- Curated raw data and performed data and statistical analysis using R or Python and employ techniques such as regressions or time-to-event analyses
- Created and presented data summaries and visualizations
- Designed and orchestrated observational studies by defining patient cohorts, study periods, endpoints, etc.
- Developed original research papers and abstracts.
- At least 2 years of cumulative programming experience (including classwork) in 1 at least one of the following:
- R
- Python
- SQL
- SAS
- STATA
- MATLAB
- Julia
- R
Preferred Qualifications:
- Post-graduate training in field
- Independent specialized research
- Management experience
- Other preferred qualifications
- Research Publications completed
Required Application Materials:
- Cover letter that describes your research interests and background
- Curriculum Vitae
- Research Publications completed (optional)
- Contact information for three references
Please apply online at https://aprecruit.ucsf.edu/JPF05389.
See Table 24B for the salary range for this position. A reasonable estimate for this position is $73,000 - $85,000.
Application Requirements
Curriculum Vitae - CV must clearly list current and/or pending qualifications (e.g. board eligibility/certification, medical licensure, etc.).
Cover Letter - that describes your research interests and background
Misc / Additional (Optional)
- 3 required (contact information only)
About UC San Francisco
As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.
UC San Francisco seeks candidates whose experience, teaching, research, or community service 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.