Remote Part-Time Data Analyst — Public Health Research

Rosepat Opportunity Manager; Northern (KY); Hybrid; USD 41,000 - 55,000; Part time

Benefits offered by this job

Pay: $35/hour

Work-from-home stipend

Equipment provided

Job summary

The Center for Violence Prevention Research seeks a part-time Data Analyst to support rigorous quantitative analyses. This role involves data cleaning and preparation, descriptive and inferential analyses, and responding to ad hoc requests across projects using survey and national surveillance data.

Ideal candidates have a Master’s in a relevant field, are proficient in R, and maintain strong data-management and reproducible-research practices.

Qualifications

• Master’s degree in statistics, epidemiology, public health, social work, psychology, data science, or related field.
• Proficiency in data management and statistical analysis using R.
• Experience cleaning, managing, and preparing datasets for analysis.
• Experience with descriptive and inferential statistical analyses.
• Familiarity with reproducible research practices, including code documentation and version control.
• Authorization to work in the United States.

Responsibilities

• Perform data cleaning and preparation for analysis.
• Conduct descriptive and preliminary statistical analyses.
• Support ad hoc analyses and data requests from team.
• Document analytic procedures and maintain reproducible workflows.
• Prepare tables, figures, and summaries for manuscripts and reports.

Skills

Data management

Statistical analysis

R programming

Data cleaning

Remote work

Education

Master’s degree in statistics, epidemiology, public health, social work, psychology, data science, or related field

Tools

R

Git

Job description

The Center for Violence Prevention Research seeks a part-time Data Analyst to support rigorous quantitative analyses. This role involves data cleaning and preparation, descriptive and inferential analyses, and responding to ad hoc requests across projects using survey and national surveillance data.

Ideal candidates have a Master’s in a relevant field, are proficient in R, and maintain strong data-management and reproducible-research practices.