Staff Associate II

The Department of Epidemiology at the Mailman School of Public Health seeks a Staff Associate II to provide data management and conduct analysis of several ongoing projects, including (1) rigorous investigation of the relationships between hypertension, its treatment, and ADRD risk among U.S. veterans, (2) statin use and ADRD risk and burden with quasi-experimental approach and machine learning methods, as well as (3) ongoing projects that explore the social determinants of Alzheimer's Disease and Related Dementias with particular attention to its cardiovascular risk factors and particularly vulnerable populations.

The ideal candidate will have extensive experience working with longitudinal data and study designs, as well as training in causal inference methods. In addition, the successful candidate should be proficient in relevant software and programming languages such as R, Python, or Stata, and possess excellent written and oral communication skills. They will provide assistance with data preparation and code development, analysis, and preparation of reports and papers for publication. As needed, they may assist developing related grant proposals and research protocols and work with team members on related projects or analyses.

Data preparation/management and code development, 25%

Detailed analyses and visualization, 50%

Preparation of reports and manuscript development for publication, 20%

Other duties as assigned, 5%

Minimum Qualifications

A Bachelor's degree in Epidemiology, Public Health, Biostatistics or a related field is required. A Master's degree or PhD is preferred.

Preferred Qualifications

Minimum of 3-4 years of experience with collecting, managing, and analyzing large-scale databases. Proficient in programming language (preferably R). Strong attention to detail and ability to manage and analyze complex data. Strong analytical and problem-solving skills. Excellent written and oral communication skills.

Columbia University is an Equal Opportunity Employer / Disability / Veteran

Pay Transparency Disclosure

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.