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    Sr./Quantitative Risk Specialist - Portland, United States - Federal Reserve System

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    Full time
    Description

    Company

    Federal Reserve Bank of San FranciscoWe are the Federal Reserve Bank of San Francisco—public servants with a mission to advance the nation's monetary, financial, and payment systems to build a stronger economy for all Americans. We are a community-engaged bank, and are committed to understanding and serving the vibrant, expansive communities of the Twelfth District. That means we seek and appreciate new perspectives. We respect people for what they do and for who they are. We build opportunities to learn and grow. When you join the SF Fed, you become part of a diverse team united in its purpose to promote an economy that works for everyone.

    The Quantitative Supervision and Research (QSR) Team within our Supervision + Credit Group provides quantitative support to the Federal Reserve's national supervisory programs in the areas of financial risk modeling and model risk management. The QSR Team engages in two primary supervisory functions, the LISCC Capital Program and the Stress Testing Program. The Team is a key contributor to the LISCC Capital Program, which is the primary supervisory group for capital adequacy and capital planning at the largest U.S. bank holding companies.

    The QSR Team is also a key contributor to the Stress Testing Program, which is responsible for developing and maintaining the Federal Reserve's financial models used in the annual Dodd-Frank Act Stress Testing (DFAST) exercise. Team members hold key roles on various modeling teams, particularly teams responsible for counterparty credit risk modeling and securities valuation modeling. This job posting is for an open position on the Counterparty Supervisory Modeling Team within the Stress Testing Program.

    With your application, please submit a resume, and GitHub link (or other) with 2 – 3 coding samples related to financial modeling. Coding samples are most helpful if they are solo-authored and represent R or Python solutions.

    Position Summary:

    The Federal Reserve System's Stress Testing Program is responsible for the annual supervisory stress-testing (DFAST) exercise. The main outcome of this exercise is the determination of firm-specific capital requirements that contribute to ensuring that the affected firms and the financial system more broadly are adequately capitalized in case of adverse economic or financial events.

    Accordingly, modelers within the Stress-Testing Program are expected to provide top-tier technical modeling expertise and high-quality model risk management skills (as per the Federal Reserve's SR 11-7 letter) to the development and maintenance of their assigned stress-testing models. Candidates are expected to have technical training in financial modeling as well as hands-on experience in the entire model development lifecycle including research, implementation, ongoing testing, performance monitoring, and operation. Candidates are also expected to have excellent coding and data science skills as well as relevant experience in the presentation and communication of quantitative modeling topics to non-technical audiences.

    This job posting is related to an open position on the Counterparty Supervisory Modeling Team (CSMT). The team is responsible for developing and maintaining the models that estimate losses due to derivative valuation adjustments (xVAs) and counterparty defaults on derivatives and securities financing transactions. Members of this team require subject matter training and expertise in the fields of asset pricing, credit risk modeling, regulatory capital treatment, and derivatives markets infrastructure.

    Essential Responsibilities:

  • Develop and maintain counterparty credit risk models relevant for supervisory stress-testing purposes.
  • Participate in all aspects of the modeling life cycle, including design, implementation, testing, production, validation, and performance assessment.
  • Perform quantitative analysis related to counterparty credit risk, including data analytics and statistical econometric modeling.
  • Develop and manage the underlying data and codebase for these models with a particular coding emphasis in R. Other coding languages are useful as well.
  • Develop and maintain model soundness and control documentation in accordance with Program standards.
  • Participate in model validation exercises by responding to queries and findings by the Federal Reserve's independent model validation function.
  • Prepare and deliver clear, accurate, and concise communication orally and in writing for quantitative and non-quantitative audiences.
  • Work collaboratively with other CSMT members and other Program staff.
  • Requirements:

  • Masters or Ph.D. degree in a quantitative field.
  • The Quantitative Specialist role typically requires three or more years of relevant experience in banking, financial industry, or banking supervision; or an equivalent combination of education and experience. The Sr. Quantitative Specialist role typically requires five or more years of experience in banking, financial industry, or banking supervision; or an equivalent combination of education and experience.
  • Previous work experience in financial risk modeling, risk measurement and management, and regulatory capital requirements.
  • Proficiency in one or more statistical programming languages, especially R.
  • Proficiency in econometric modeling techniques and working with large data sets.
  • Well-developed organizational, communication, and collaboration skills.
  • Demonstrated experience in credit risk modeling, credit risk management, risk measurement techniques, market-based regulatory capital requirements, and asset pricing.
  • Demonstrated ability to set priorities as well as execute in a timely manner priorities as set by/with more senior management.
  • This position requires access to confidential supervisory information, which is limited to "Protected Individuals." Protected Individuals include, but are not limited to, U.S. citizens and U.S. nationals, U.S. permanent residents who are not yet eligible to apply for naturalization, and U.S. permanent residents who have applied for naturalization within six months of being eligible to do so or who will sign a declaration of intent to apply for naturalization before they begin employment.
  • ** With your application, please submit a resume, and GitHub link (or other) with 2 – 3 coding samples related to financial modeling. Coding samples are most helpful if they are solo-authored and represent R or Python solutions. **

    #LI-Hybrid

    Base Salary Range for Quantitative Specialist: Min: $127,400 Mid: $167,800 Max: $208,500

    (Location: San Francisco)

    Base Salary Range for Sr. Quantitative Specialist Min: Min: $151,500 Mid: $196,700 Max: $241,900

    (Location: San Francisco)

    Final salary and offer will be determined by the applicant's background, experience, skills, internal equity, and alignment with geographic and other market data.

    Full Time / Part Time

    Full time

    Regular / Temporary

    Regular

    Job Exempt (Yes / No)

    Yes

    Job Category

    Monetary And Economic Policy

    Work Shift

    First (United States of America)

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