Supplemental Information
Profile #1
The ideal candidate for this position has a background in Marketing or Economics and a strong interest in the application of econometric methods to the study of marketing problems, including but not limited to advertising, platforms, and demand/supply estimation.
A successful candidate has:
- Familiarity with the concepts of causal inference, including both experimental and non-experimental econometric methods
- Demonstrated interest in the topics of Industrial Organization and/or Digital Economics
- Familiarity with working with large panel and cross-sectional data
- Experience with experimentation in digital advertising platforms (e.g., Meta, Google, etc.)
Profile #2
The ideal candidate for this position has a background in Marketing or Computer Science and a strong interest in the application of machine learning techniques to the study of marketing problems, including but not limited to the analysis of consumer behavior, user-generated content, and advertising.
A successful candidate has:
- Familiarity with text parsing and analysis (natural language processing) and machine learning techniques
- Programming experience in Python and one or more of the following languages: Java, SQL, SAS, Matlab, and/or C++
- Familiarity with working with unstructured data and APIs
- Experience with experimentation in digital advertising platforms (e.g., Meta, Google, etc.)