As an Empirical Research Fellow, you will work with faculty at the Kellogg School of Management on the preparation and analysis of data for economics-based research projects. You will generally work on a few projects at a time, with multiple faculty members, and your contributions could span all aspects of the research life cycle.
Your research duties will vary, but may include: collecting and validating new research datasets, performing statistical analyses on large databases, writing programs to simulate results of theoretical models, preparing results for inclusion in presentations and publications, or updating existing code for greater efficiency or easier reproducibility.
If selected, you will be offered a one-year appointment, with the ability to renew for a second year based on performance. Successful applicants must have completed at least a bachelor’s degree by the employment start date.
Your application should include a cover letter that describes your academic career goals and how a pre-doctoral appointment as an Empirical Research Fellow will serve those goals.
We seek applicants who have an interest in applying for a Ph.D. program in Economics, Finance, Operations Research, or a related field in the pursuit of an academic research career. The ideal candidate will have: (i) strong data management and computer programming skills; (ii) exposure to applied statistical models; and, (iii) prior experience working on research, such as an independent thesis or as a research assistant. Prior coursework in Economics is a plus, but not necessary; in fact, we feel this position is well suited for someone who possesses strong quantitative skills and wants more exposure to Economics or Finance.
Work closely with faculty members as project team members on new or ongoing research projects.
Collect, maintain, and document original research datasets.
As necessary, merge together data from separate sources, derive new variables, or reformat data for analysis.
Proactively test data for integrity.
Create or replicate results of applied statistical or machine learning models.
Write programs to simulate the results of theoretical model and/or to solve constrained optimization problems.
Produce tables, figures, and/or other research outputs as needed.
Might assist faculty members with literature reviews or reviewing drafts of papers.
Successful completion of a full 4-year course of study in an accredited college or university, leading to a bachelor’s or higher degree.
A long-term interest in conducting research in Economics, Finance, or a related field.
Ability to write code in at least one commonly used statistical programming language – such as R, Python, Stata, SAS, and/or Matlab.
Strong habits documenting and managing versions of datasets and program code.
Demonstrated ability to work independently to solve analytical problems.
Good understanding of applied statistical concepts.
Prior experience working as a research assistant on a faculty research project or working independently on one’s own original research project.
Working knowledge of how to query and manipulate various data in various formats or data structures.
Experience working with lower-level or scripting programming languages – such as Python, bash, Java, or C.
Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes, including veterans and individuals with disabilities. Women, racial and ethnic minorities, individuals with disabilities, and veterans are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.
Internal Number: 39434
About Northwestern University
Northwestern University is a major private research university with 12 academic divisions located on three campuses in Evanston, Chicago, and Education City in Doha, Qatar. We have approximately 2,500 full-time faculty members, 17,000 graduate and undergraduate students, and over 5,700 full and part-time staff. Northwestern University combines innovative teaching and pioneering research in a highly collaborative environment. It provides students and faculty exceptional opportunities for intellectual, personal and professional growth.