SRC Graduate Intern Program in Data Science
The Federal Reserve Bank of Minneapolis Graduate Intern Program in Data Science is intended to introduce full-time or part-time graduate students to the broader Federal Reserve System and, more specifically, the use of Data Science in the Banking Supervision function. Being at the forefront of overseeing the nation’s largest and most complex financial institutions is a unique opportunity that requires highly analytical and quantitative individuals. Interns will gain exposure to and experience with the most important quantitative issues and challenges currently facing the regulatory and financial industries.
Interns will be placed in either of two units: The System Analytics unit or the Stress Testing unit.
Interns placed in the System Analytics unit will work with staff to build work products such as dashboards and reports that process large amounts of banking and macroeconomic data and synthesize it into a succinct risk assessment. Candidates with appropriate skill sets may also utilize advanced statistical techniques and/or machine learning to analyze big data to assess conditions in the banking sector.
Interns placed in the Stress Testing unit will work with staff to create interactive analytics reports that summarize current risk in large bank balance sheets, severity of the stress test scenarios, and model-projected bank performance. They will implement stress testing model changes in production-quality code, assist in implementation testing, and support creation of technical documentation.
The Intern Program provides an opportunity to work in an intellectually stimulating and collaborative environment, to engage in meaningful public service, and to interact with senior leaders at the Minneapolis Fed. Upon completion of their graduate degree, Interns will have a strong basis of experience to inform a future career in quantitative finance in the Banking sector.
Training and professional development components:
- Learn to manage, manipulate, interpret and analyze trends in large sets of data and methodology documents
- Handle and summarize large amounts of macroeconomic and banking data
- Become familiar with different metrics and measures that are used to evaluate the health of the Banking system
- Utilize knowledge to synthesize information and glean insights related to Banking conditions around the country
- Present technical issues to non-technical audiences and to clearly articulate findings in verbal and written form
This internship will start in June and will go through the summer of 2021.
Qualifications – External
- Relevant course work towards a graduate degree in math- or quantitative-related fields such as Economics, Engineering, Mathematics, Computer Science, Quantitative Finance, Statistics, Data Science, Business Administration, etc.
- Strong academic record
- Knowledge of query languages such as SQL is required
- Knowledge of statistical programming languages such as R, Python, Matlab, or Stata is required; R knowledge is preferred including development experience in Shiny and reporting experience using R Markdown
- Knowledge of analytics engines such as Tableau and PowerBI is a plus, but not required
- Knowledge of machine learning techniques a plus, but not required
- Knowledge of collaborative version control platforms such as GitLab is a plus, but not required
- Knowledge of Finance and Banking a plus, but not required
- Ability to work independently without extensive oversight as well as the aptitude to collaboratively function within a team
- Ability to fulfill 500 hours of work under the Intern Program
- Meet Protected Individual requirement