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Intern, Quantitative Risk Analysis -RBOPS - R025241 Primary Location : DC-Washington : Employee Status : Temporary Overtime Status : Non-exempt Job Type : Internship : : : Relocation Provided: : No Compensation Grade Low: : FH Pay Grade 20 Compensation Grade High: : FH Pay Grade 22 Minimum Salary: : $25.58 Maximum Salary: : $39.42 Posting Date : Oct 1, 2025 Position Description Minimum Education Enrolled in an undergraduate or graduate degree program at an accredited university and returning to continue studies after the internship. Minimum Experience 0 Summary The Federal Reserve Board (Board) provides students opportunities for career success. The Board’s Internship program is designed to provide valuable work experience for undergraduate and graduate students considering careers including, but not limited to, economics, finance and accounting, information systems, and data analysis. The Board believes that by combining academic endeavors with project-related work experience, qualified and capable college students can gain the practical knowledge need in a competitive global job market. Internships are paid positions with salaries commensurate with credit hours; internships may be in-person, remote or hybrid, depending on the needs of the team. Employment in the Board’s internship program is granted to U.S. citizens. Applicants must be currently enrolled in an undergraduate or graduate degree program at an accredited university and returning to continue studies after the internship. Interns receive a syllabus or research project plan outlining their projects and goals for the internship. Interns are assigned a supervisor or mentor to guide them through their internship, and regular check-in meetings with their manager to manage performance expectations and assist with learning goals. Interns have access to a wide range of training programs and events for professional development purposes. Position Requirements Qualifications: The Quantitative Risk Analysis section is responsible for assessing quantitative risk methodologies developed by the financial sector, or the Reserve Banks, to measure and manage credit, liquidity, counterparty, and market risks, as well as value collateral. The program analyzes risks and contributes to policies and research related to the clearing and settling of payments, securities, financial derivatives, and other financial instruments. The program monitors and evaluates the quantitative risk management of financial market infrastructures (FMIs), financial institutions engaged in systemically important payment, clearing, and settlement (PCS) activities, and the Reserve Banks. The program contributes to quantitative risk research, particularly topics related to FMIs and systemically important PCS activities, and to systemic risk analysis. Expected Projects: • Deep Neural Networks vs. Nonlinear econometric models: a project to explore performances of Neural Networks against a selected set of nonlinear econometric models in practical applications and by using extensive Monte Carlo simulations Competencies/Learning Objectives: • Excel in data representation, manipulation, analysis • Design, train, validate, test and tune Deep Learning and econometric models for empirical analysis to answer questions in economics and finance Required Skills and Knowledge: • BSc or Graduate (Masters or PhD) student in Computer Science, Economics, Business, or any other engineering or science field • Completed courses on Data Science, Econometrics, and Machine Learning • Familiarity with Python and/or R • Interest in economic and financial data and research • Familiarity with data manipulation, model development, training, validation, and testing approaches • Interest in economic and financial time series analysis and econometrics Preferred Skills : • Experienced in working with time series data and conducting research in economics and econometrics • Written scripts to design and develop Machine Learning and econometric models • Completed at least one course on Data Science, Machine Learning, Econometrics, or Deep Learning or relevant classes Required Documents for application:  CV and two reference letters. A copy of an unofficial transcript may be requested. Suggested Major/Minor : Economics, Finance, Computer Science, Data Science, Machine Learning Keywords: finance, computer science, data science, statistics Notes: US Citizenship is required  for all Board internships and applicants must be current students, graduating from their program August 2026 or later. Proof of enrollment will be required. This internship must be completed in-person in Washington, DC. Candidates must be able to work at a minimum of 20 hours per week during the school year, 40 hours per week during the summer This internship duration shall not exceed 180 days from a candidate's start date.  Learn more about our internship program: https://www.federalreserve.gov/careers-internships.htm We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment on the basis of race, color, religion, sex, pregnancy, national origin, age, disability, genetic information, or application, membership, or service in the uniformed services. Req ID: R025241