Position Summary
The Variable hours officer will support research projects examining sociobiologic mechanisms underlying cancer outcomes, with a focus on understanding how social, environmental, and biological factors jointly shape cancer risk, progression, and survivorship. The VHO will manage, integrate, and analyze complex datasets, including epidemiologic, biomarkers, and molecular data, to generate insights that inform cancer disparities research. This position provides an exciting opportunity to work…
within a multidisciplinary research environment that bridges epidemiology, biostatistics, molecular biology, and social and behavioral sciences.
Responsibilities
- Manage and maintain large, multi-level datasets linking social, clinical, and biological data ? 70%
- Conduct descriptive, multivariable, and multi-level analyses to examine relationships between social determinants, biological pathways, and cancer outcomes
- Collaborate on the integration of data from diverse sources, including cohort studies (e.g., Women’s Health Initiative), electronic health records, and biospecimen repositories
- Develop and document reproducible workflows for data management, quality control, and statistical analysis
- Generate analytic summaries, tables, figures, and visualizations and contribute to the development of manuscripts, presentations, and grant applications ? 10%
- Work closely with faculty and trainees to refine research questions and design analytic strategies that align with study aims ? 10%
- Participate in team meetings and collaborative research discussions ? 5%
- Perform additional duties as required in support of program objectives ? 5%
Minimum Qualifications
- Bachelor's degree or equivalent in education and experience.
Preferred Qualifications
- Master’s degree in Biostatistics, Epidemiology, Statistics, or Data Science, or a related quantitative discipline.
- Proficiency in at least one statistical programming language (e.g., R, SAS, or Stata).
- Experience in data management, cleaning, and integration across multiple data types (e.g., survey, clinical, biomarker, or genomic).
- Strong foundation in regression modeling and inferential statistics.
- Excellent organizational, analytical, and communications skills.
- Ability to work collaboratively in an interdisciplinary research team.
- Experience analyzing multi-level, biomarker, or “omics data within population-based studies.
- Familiarity with epidemiologic methods or mediation or pathway analysis.
- Experience with data visualization tools.
- Understanding of social determinants of health and their integration into biological or molecular analyses.
Equal Opportunity Employer / Disability / Veteran
Columbia University is committed to the hiring of qualified local residents.
