Statistician

Life-saving breakthroughs, innovative therapies, and next-generation technologies. Through vision, tenacity, and inspiration, UCLA Health's world-class researchers are redefining human health and patient care. Join us and live out your passion for discovery while making an incredible difference in the lives of people around the world.

The Data Analyst is responsible for building, managing, and analyzing complex datasets, including large-scale electronic health record (EHR) and Medicare data. This role involves data construction, cleaning, quality control, and advanced statistical analysis to support a variety of research projects.

Key responsibilities include collaborating with faculty and staff on database design, statistical modeling, and data management. The analyst will also deliver tailored statistical analyses and present findings through clear graphical and tabular summaries.

This position is ideal for someone who enjoys working with large datasets, solving analytical challenges, and contributing to impactful research through high-quality data insights.

Salary: $33.96 - $69.54 hourly

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., STATA, R, SAS).
  
• 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.
  
• Ability to combine data from different data tables and different data sources into a single file
  
• Competency in SQL