Data Analyst Job at Columbia University Irving Medical Center in New York

Overview

Join to apply for the Data Analyst role at Columbia University Irving Medical Center. The Center for Infection and Immunity (CII) at CUIMC is seeking a Data Analyst I to support translational research on acute and chronic viral infections focusing on high-throughput serology and reactivation of latent viruses in chronic diseases.

The successful candidate will contribute to the design and optimization of serologic assays/platforms and the development of data pipelines using advanced statistical and machine learning methods. This position supports federally and foundation-funded initiatives applying peptide-based phage display and high-density peptide microarray platforms to understand immune responses to viral infections in both human and animal populations (One Health). The analyst will work under the supervision of CII faculty and closely collaborate with research scientists, statisticians, and clinical investigators across Columbia and partner institutions.

CII is among the world’s leading centers for basic and translational science in infectious and immune-mediated diseases. The ideal candidate will demonstrate strong analytical skills, attention to detail, and the ability to adapt in a fast-paced, evolving research environment.

Responsibilities

• Design and analyze high-throughput serological datasets; develop and refine automated analysis pipelines using machine learning/AI methods – 40%
• Perform basic and advanced statistical analysis, including sample size and power calculations for serological studies – 20%
• Generate data visualizations and figures for use in manuscripts, grants, and presentations – 20%
• Provide bioinformatic support for projects involving microbial detection, immune profiling, and virus discovery – 10%
• Conduct quality control and data management tasks for clinical, laboratory, and survey-based datasets – 10%

Minimum Qualifications

• Bachelor’s degree or equivalent in education and experience, plus 2 years of related experience
• A Master’s degree in epidemiology, biostatistics, public health, or a related field may substitute for required experience
• Proficiency in R and Python for statistical analysis and modeling
• Familiarity with machine learning tools such as forward selection, XGBoost, Random Forest, and DESeq2

Preferred Qualifications

• Experience with phage display systems, peptide microarrays, or multiplex serology
• Background in immunology, virology, infectious disease, or aging research
• Advanced statistical skills (e.g., multi-level models, Bayesian inference, latent class analysis)
• Strong data visualization skills using packages such as ggplot2, seaborn, or matplotlib
• Experience with clinical research databases and data integration
• Familiarity with SPSS is a plus but not required

Equal Opportunity Employer / Disability / Veteran