Hybrid Health Data Analyst: R/SAS & Manuscripts

Rutgers University; New Brunswick (NJ); Hybrid; USD 74,000 - 106,000; Full time

Benefits offered by this job

Medical benefits

Paid vacation and holidays

Retirement benefits

Educational benefits

Life insurance

Employee discount programs

Job summary

Rutgers University in the Department of Psychiatry at the Robert Wood Johnson Medical School is seeking a Data Analyst to support investigators with data management and statistical analysis across studies on alcohol and drug use and health outcomes.

The role includes contributing to manuscript methods and results as a co-author, collaborating with biostatisticians, and writing code in R or SAS for data preparation, analysis, and figure generation.

Qualifications

• Bachelor’s degree in a related field with three years of data design/analysis experience.
• Experience preparing data for analysis and conducting statistical analyses.
• Proficiency with MS Office, especially Excel and Word.
• Ability to program, manage data, and interpret results for reports.

Responsibilities

• Prepare datasets and documentation for statistical analyses.
• Design data validity tests and analysis processes.
• Perform descriptive and multivariable analyses with the team.
• Work with clinical and observational data across multiple studies.
• Collaborate to interpret findings and present data summaries.
• Write code in R/SAS for data prep, analysis, and generating figures and tables.
• Attend meetings and help draft methods and results for manuscripts.

Skills

Three years of experience

Microsoft Office

Excel

Word

Programming

Education

Bachelor’s Degree

Master’s degree preferred

Tools

R

SAS

REDCap

Qualtrics

Microsoft Office

Excel

Word

Job description

Rutgers University in the Department of Psychiatry at the Robert Wood Johnson Medical School is seeking a Data Analyst to support investigators with data management and statistical analysis across studies on alcohol and drug use and health outcomes.

The role includes contributing to manuscript methods and results as a co-author, collaborating with biostatisticians, and writing code in R or SAS for data preparation, analysis, and figure generation.