Economic Research Associate: Data, Models & Policy

Federal Reserve Bank of New York

Richmond (VA)

On-site

USD 60,000 - 74,000

Full time

9 days ago
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Benefits offered by this job

Great medical benefits
Pension and 401(k) with employer match
Paid time off
Tuition reimbursement
Paid volunteer leave
Onsite amenities

Job summary

The Federal Reserve Bank of Richmond seeks highly motivated recent graduates to join its Research Department as a two-year Research Associate. You will work closely with economists on academic and policy-oriented research, conducting data analysis, coding, and literature reviews in a mentorship-rich environment.

Two roles exist: a Richmond-based RA and a DC-based RA with quarterly travel to Richmond. The program emphasizes learning, seminars, and collaboration across projects, with robust

Qualifications

  • Bachelor's degree in economics, statistics, and mathematics coursework is preferred.
  • GPA of 3.5 or higher required for consideration.
  • Experience with computer programming and statistical software (Stata, R, Matlab) is valued.

Responsibilities

  • Write computer code to solve dynamic economic models.
  • Analyze time-series and panel data.
  • Write literature reviews for research topics.
  • Assist in model derivations and development.
  • Prepare policy briefings and summarize research findings.
  • Engage in new long-term projects and collaborate on short-term tasks as needed.

Skills

Economics
Econometrics
Mathematics
Programming

Education

Bachelor's degree in Economics
GPA 3.5+

Tools

Stata
R
Matlab

Job description

The Federal Reserve Bank of Richmond seeks highly motivated recent graduates to join its Research Department as a two-year Research Associate. You will work closely with economists on academic and policy-oriented research, conducting data analysis, coding, and literature reviews in a mentorship-rich environment.

Two roles exist: a Richmond-based RA and a DC-based RA with quarterly travel to Richmond. The program emphasizes learning, seminars, and collaboration across projects, with robust

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