Quantitative Risk Specialist
Federal Reserve Bank Of Kansas City
Los Angeles, San Francisco
hace 2 días

Shift

Day JobJob SensitivityTier II - Credit Check

The Federal Reserve Bank of San Francisco believes in the diversity of our people, ideas, and experiences and is committed to building an inclusive culture that is representative of the communities we serve.

Overview

The Financial Institution Supervision and Credit (FISC) Division at the Federal Reserve Bank of San Francisco supervises financial institutions, and service providers to financial institutions, in the 12th Federal Reserve District.

Our mission is to ensure a safe, sound, and accessible financial system. The Suptech ST’ Team within the Risk, Policy, and Analysis Group is newly created to directly support FISC’s strategic objective of deepening our knowledge of, and thought leadership in, the utilization of new and evolving technologies in our supervisory programs and examination processes.

This cross-disciplinary team of developers and / or data scientists collaborates with colleagues throughout FISC to identify product development opportunities, design solutions, and facilitate their implementation.

ST additionally has education and advocacy responsibilities which in part support near- to intermediate-term training of, or improve efficiency of, generalists responsible for examining all Low Risk, and most Moderate Risk, RBO and CBO firms, and across all risk stripes (including IT and BSA, but also Non-IT Ops, Credit, etc.).

Job Summary

The Quantitative Risk Specialist serves as a technical subject matter expert for, and practitioner of, applied data science.

The position requires providing critical input in helping to lead, identify and develop applied data science opportunities across Supervision Business Lines, with a focus on institutions supervised by the Twelfth District’s Regional, Community and Foreign Examinations Group.

The role requires closely working with multiple teams and various business stakeholders throughout the Bank to deliver on the FRB-

SF’s overall Mission but especially FISC’s vision, strategy, and related objectives for developing and implementing innovative solutions to business problems that support the efficiency and efficacy our supervisory program and examination processes.

Duties and Responsibilities :

Build ingestion processes to prepare, extract, and enrich a variety of structured and unstructured data sources such as, news, internal / external documents, external financial information, and confidential supervisory information.

Perform exploratory data analysis, generate and test working hypotheses, and document and discuss interesting trends and relationships to a variety of audiences.

Develop, document & maintain statistical, financial and / or econometric models to analyze capital, asset quality, earnings, liquidity risk exposure, or other sophisticated concepts, including non-

financial risks, at banking institutions.

Communicate / Present results using various media to both technical and non-technical audiences, and visualizing data to communicate complex ideas in FISC and Technology.

Provide analytical support to development of innovative solutions leveraging emerging technologies to support evolving needs of supervision and examination management and staff.

  • Deliver on Supervisory engagement milestones by following analytics processes to mitigate risks in data, modeling, validation, and delivery;
  • manage assumptions, and risks, and work with others to clear issues.

    Position Requirements

    Established ability to work with large structured and unstructured financial data sets and have the required statistical skills to analyze and prepare them for modeling and algorithm development.

    4+ years of direct or comparable banking, financial industry, or banking supervision experience with a focus in a risk specialty area.

    3+ years of experience in a data science / modeler / analyst role specifically focused on financial regulation.

    2+ years of experience in working at financial regulatory institutions with large datasets to build models and algorithms with open source technologies.

    Strong statistical modelling and programming skills in R or Python.

    Proficiency in SQL - able to write structured and efficient queries on large data sets.

    Comfortable working in a loosely structured organization and advancing multiple projects at once on a tight schedule.

    Ability to share results with a non-technical audience

    Excellent collaborator with strong written and verbal communication skills

    Experience with data visualization packages (e.g. ggplot2, plotly)

    Experience building interactive dashboards and apps (e.g. Shiny) is a plus but not required

    Familiarity with model development lifecycle, and in particular model validation processes (e.g. SR 11-7)

    A passion for statistics, forecasting is also a plus but also not required

    Bachelor’s and Master's Degree preferably in Business / Finance or an analytical field such as Economics, Mathematics, Engineering, Computer Science.

    Behavioral Competencies

  • Candidate should be able to demonstrate the following Behavioral Competencies : Critical Thinking, Collaboration, Influence, Achievement, and Innovation
  • The Federal Reserve Bank of San Francisco is an Equal Opportunity Employer.

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