Columbia Business School is seeking to hire one or more Staff Associates of for the Economics Division. The work will include quantitative and qualitative research and analysis involving the collection, coordination, and management of information and data. This position provides an opportunity to gain experience in academic economics research and would be ideal preparation for a Ph.D. program in economics or other related fields. This is a two-year position with a possible extension to a third-year.

The Staff Associate duties involve work in one or more of the following areas of research: economics, and statistics. Specific duties include:

• Collect, clean, and maintain datasets and databases. Extract and link data from multiple databases for analysis. Prepare detailed documentation.

• Develop models and implement program code (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 the preparation of reports, journal articles, presentations, websites, and other research outlets.

• Perform case-based research, including work with detailed primary documents.

Applicants for Staff Associate position are expected to have the following:

• Programming experience in STATA is required. Strong preference for those who also know Python.

• Additional programming experience in one or more of the following languages: R, SQL, SAS, Matlab, and/or C++ is preferred.

• Familiarity with statistical tools such as linear regression is required.

• Demonstrated exceptional written and oral communications skills needed – a writing sample is required.

Minimum Degree Required:

Bachelor’s degree in Economics or Finance or in a quantitative discipline such as Mathematics, Statistics, Engineering with coursework in Economics and Finance.

Minimum Qualifications:

Up to two years of research experience in a research role as a research assistant during the academic year or a summer internship in a research lab or governmental institution.