Research Data Analyst

General Information

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Work Location: Los Angeles, USA

Onsite or Remote

Fully Remote

Work Schedule

Monday-Friday, 8:00am-5:00pm

Posted Date

06/20/2024

Salary Range: $31.03 - 65.9 Hourly

Employment Type

2 - Staff: Career

Duration

Indefinite

Job #

17453

Primary Duties and Responsibilities

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The Department of Medicine is seeking a skilled Research Data Analyst to enhance our data management and statistical analysis capabilities. The successful candidate will be responsible for constructing, managing, and analyzing data, ensuring data quality control, and designing study databases. This role involves close collaboration with staff and faculty to provide tailored statistical analyses, develop statistical models, and contribute to the statistical sections of manuscripts and grant applications. The analyst will also summarize complex statistical findings, ensuring they are accessible and actionable for research purposes.

Hourly range: $31.03-$65.90

Job Qualifications

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Required:

• Bachelor's degree in Statistics/Computer Science/Bioinformatics/Data Specification/ Data Science/Computational or equivalent 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.