Data Scientist - Urology

Drive Impactful Healthcare Research Through Data
Science and Analytics

The David Geffen School
of Medicine at UCLA, Department of Urology is seeking a full-time Data
Scientist to support transformative research initiatives that improve healthcare
delivery and population health. This role is ideal for professionals who
combine programming, statistical expertise, and domain knowledge to solve
complex problems and guide data-informed decision-making.

As a key member of our
research team, you'll work with faculty and staff to analyze large healthcare
datasets, build predictive models, and communicate insights that shape clinical
practice and policy.

We're looking for
someone who thrives in a collaborative, fast-paced environment, brings
strategic thinking and technical expertise, and is passionate about using data
to improve lives.

Join us in shaping the
future of healthcare through data science and innovation. Apply today and
become part of a dynamic team at the forefront of population-health research.

Hourly Salary Range: $33.96
- $69.54

Required:

* Bachelor's degree in Statistics/Computer
Science/Bioinformatics/Data Specification/ Data Science/Computational or
equivalent combination of education and experience.

* 1-2 years of experience in Statistics/Computer
Science/Bioinformatics/Data Specification/ Data Science.

* Knowledge of basic and multivariate statistics.

* Knowledge of research design.

* Competency in statistical software applications (e.g., R, SAS,
STATA).

* Ability to conceptualize and construct tables and graphs.

* Working knowledge of statistical and/or medical terminology.

* Ability to summarize statistical analyses for collaborators.

* Knowledge of statistical techniques.

* Ability to utilize database management software to run queries and
extract data.

* Ability to construct databases.

* Ability to produce visual tools and dashboards that highlight the
essential information from a project or study.

* Knowledge of basic office software and applications (e.g.,
Microsoft Office Suite, Google, Internet search engines, etc.).

* Ability to learn new statistical techniques and to adapt existing
code to customize statistical analysis strategies.