Staff Associate - Decision, Risk, and Operations

Overview

Columbia Business School seeks a Staff Associate of research for the Decision, Risk, and Operations (DRO) Division. The role focuses on quantitative and qualitative research, data collection, computer model development, and special projects within the division.

• Collect, clean, and maintain datasets and databases; extract and link data from multiple sources.
• Develop models and implement program code using STATA, Python, SQL, R, SAS, Matlab, etc.
• Perform statistical analysis, including regression analysis and machine learning techniques.
• Assist with data analysis and dissemination of findings through reports, journal articles, presentations, websites, and other research outlets.
• Conduct case-based research with detailed primary documents.

• Bachelor’s degree in Economics, Finance, Mathematics, Statistics, Engineering, Computer Science, Data Science, or a related quantitative discipline.
• At least 6 months of experience in a research role or as a research assistant.
• Programming experience in STATA is required; strong preference for Python or R.
• Additional programming experience in SQL, SAS, Matlab, or C is preferred.
• Familiarity with statistical tools such as linear regression is required.
• Exceptional written and oral communication skills; a writing sample is required.
• Expertise in processing large volumes of data and algorithm design.
• Experience in market design applications preferred.
• Knowledge of text parsing, natural language processing, or machine learning techniques is preferred.
• Ability to work on multiple projects simultaneously.

Columbia University is an Equal Opportunity Employer, including for Disability and Veteran applicants.

Pay Transparency Disclosure

The salary for this role will be set based on a variety of factors, including 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.