Data Analyst

Columbia University is hiring a Data Analyst to support a Principal Investigator (PI) with data and sample management for epidemiologic studies. The role focuses on preparing datasets for analysis, running statistical work for scientific outputs, and improving how samples and images are tracked and quality-controlled.

This is an onsite position in New York, NY with a salary range of USD 70,000 to 80,000 per year. The position requires at least 3 years of related experience and a Bachelor’s degree or equivalent education and experience.

What you’ll do

• Manage and clean existing datasets used in epidemiologic research.
• Run statistical analyses to support progress reports and abstracts/manuscripts.
• Assemble and review relevant literature from related studies.
• Prepare documentation required for regulatory and IRB review.
• Create and maintain databases for samples and images stored for study use.
• Develop tracking systems and support quality control for samples.
• Contribute new ideas for manuscript development and future studies.
• Provide statistical analysis support to the study team.
• Perform other related duties and responsibilities as assigned or requested.

Key responsibilities in the day-to-day

• Support the PI with managing and analyzing data and samples from planned, ongoing, and completed epidemiologic studies.
• Clean and create databases for completed studies, including appropriate documentation.
• Build analytic databases and support statistical write-ups for reports, abstracts, and manuscripts.
• Establish systems for tracking samples, images, and other data, while developing quality control systems.
• Independently design, initiate, and conduct statistical analyses for publication write-ups and planning for future studies.

Skills and tools

• R-Studio
• SAS

Requirements

• Bachelor’s degree or equivalent in education and experience, plus three years of related experience.

Preferred qualifications

• Bachelor’s degree in a quantitative field.
• Experience managing and analyzing data from epidemiologic studies.
• Proficiency in R-Studio or SAS for statistical analysis.