Research Data Analyst II - Radiation Oncology

General Information

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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

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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:

• Medical Expenditure Panel Survey
• 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

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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.