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General Information

Work Location: Los Angeles, USA
Onsite or Remote
Fully On-Site
Work Schedule
Monday - Friday, 8:00am - 5:00pm
Posted Date
04/15/2024
Salary Range: $31.03 - 65.9 Hourly
Employment Type
2 - Staff: Career
Duration
Indefinite
Job #
14986

Primary Duties and Responsibilities

Join our dynamic team as a Research Data Analyst Assistant, where you'll play a crucial role in constructing and managing data for impactful projects. Dive into the world of statistical analysis while collaborating with esteemed staff and faculty.

Your primary responsibilities will include:

  • Ensuring data quality
  • Designing study databases
  • Work alongside experts to deliver tailored statistical analyses
  • Craft compelling sections for manuscripts and grant applications
  • Summarize findings

The ideal candidate would have experience working with the following databases:

  1. Medical Expenditure Panel Survey
  2. SEER-Medicare

If you're passionate about making a difference in cancer health economics research through data-driven approaches, this is the opportunity for you. Be a part of our groundbreaking work!

Salary: $31.03 - $65.90/hour

Job Qualifications

Required:

  • Bachelor's degree in Biostatistics/Statistics/Health Economics/Health Services Research or equivalent experience.
  • 1-2 years of experience in Biostatistics/Statistics/Health Economics/Health Services Research / 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 econometric analysis of medical cost data.
  • Ability to summarize statistical analyses for collaborators.
  • Ability to utilize database management software to run queries, extract data, and construt study cohorts from large administrative 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/econometric analysis strategies.