Quantitative Credit Analyst, Assoc. Dir.

The Federal Home Loan Bank of San Francisco (the "Bank") is a cooperative, wholesale bank that provides liquidity to its members and helps meet community credit needs by providing credit products and services to member financial institutions through all phases of the economic cycle. The Bank's members include large and regional commercial banks, community banks, credit unions, industrial loan companies, savings institutions, insurance companies, and community development financial institutions headquartered in Arizona, California, and Nevada. The Bank is member-focused; embraces accountability to meet commitments and upholds our governance, risk and control standards as a government sponsored enterprise; and values differences to foster an inclusive culture.

Position
The Associate Director, Quantitative Credit Risk Analyst, provides data driven analyses in support of the Credit Risk Management department. This includes, but is not limited to, various quantitative initiatives such as the development of analytical tools or frameworks and advanced statistical models to enhance the credit underwriting, risk rating, and surveillance process. The individual will be the model owner and responsible for model performance monitoring, recalibration, and validation efforts, and be the point person for independent validators, auditors, and regulators. In this role, the individual is also expected to collaborate with the credit operations/system/data team and provide tactical and strategic direction for credit data management and analysis, as well as credit underwriting system configuration and information dashboarding.

The successful candidate must be an experienced professional with both strong credit fundamentals and quantitative skills, who can deliver a high-quality product, individually and/or through a team. They will support a practice to create data-driven processes and implement an enhanced credit underwriting framework.

The quantitative enhancement of the credit underwriting and risk management processes is part of the Bank's multi-year strategy in transforming its people, data, and technology while maintaining strong governance culture and adhering to Federal Housing Finance Agency (FHFA) regulations and other regulatory guidelines.

Major Accountabilities:

• Apply quantitative techniques to develop and validate credit risk modeling methodologies and perform the practical application of advanced analytics techniques to help with individual obligor and portfolio credit risk assessments and decision processes, including pro forma and scenario analysis.
• Integrate analytical tools and credit models into the underwriting system for more streamlined and automated risk management processes and workflows. Enhance credit information management system and information dashboards.
• Deliver quantitative support for credit risk management and governance, which includes model development and implementation, documentation, and performance benchmarking, while establishing relationships with team members and stake holders at appropriate levels.
• Develop and maintain advanced statistical credit models to risk rate the Bank's credit obligors in compliance with the Bank's Model Risk Management Policy. This is inclusive of proper model documentation, procedures, controls, and performance reporting, as well as the provisioning of 3rd party benchmark and challenger models, related business unit validations, and maintenance of the vendor relationships.
• Assists management with credit risk oversight, preparation of risk analysis and reports, and meeting compliance deadlines and requirements related to exam, audit, and model validation recommendations.
• Assist with enhancements to the Risk Rating Framework and rating definitions in alignment with risk rating models.
• Utilize best modeling practices and methodologies in the areas of data processing, sampling, model design/specification, model performance assessment, and evaluation testing
• Perform data analysis and collaborate with stakeholders throughout the model development process to inform decision making.
• Preparing high-quality deliverables such as model development documentation and implementation materials while meeting established deadlines.

Qualifications

• MA/MS or PhD in Statistics, Economics, Finance, Mathematics, or related quantitative field highly preferred, plus 5 years of experience in credit risk modeling and associated methodologies and their role in the overall risk management framework; demonstrate knowledge of the risk management function and the model lifecycle.
• Subject matter knowledge of quantitative and qualitative risk factors, industry risks, and risk management approaches with focus on credit risk management.
• Programming languages used for statistical analysis and data programming including R, Python, Excel, VBA, BitBucket, and SQL (both Oracle SQL and MS SQL). Familiarity with predictive modeling using statistical and/or machine learning techniques.
• Familiarity in setting up production code in Amazon Web Services (AWS) platforms such as SageMaker Studio, SageMaker, S3, lambda, EMR, and RDS is a plus.
• Knowledge of industry standards for financial institution credit risk models such as Moody's RiskCalc Banks and Credit Union Private company models, Insurance P&C/Life and Health models, Moody's CreditEdge, S&P Credit Analytics models, Bloomberg DRSK, and KBRA's KFI model.
• Experience with, or understanding of, assessing credit risk associated with lending to non-regulated mortgage lenders/investors, Community Development Institutions, mortgage Real Estate Investment Trusts (REITs) and Insurance Companies
• Familiarity with market data such as SEC 10-K/Q filings, bank holding company filings, bank (FDIC), credit union (NCUA), and insurance (NAIC) regulatory financial reporting (call reports), and credit data providers (such as SNL Financial/S&P Capital IQ/Market Intelligence and Aeris for Community Financial Development Institutions).
• Familiarity with NRSRO and other credit rating methodologies both from fundamental and quantitative perspectives.

Critical Competencies:

The successful candidate will be a creative problem solver with an innovative mindset and possess a balance of strong credit risk analysis and business skills. Must have:

• Strong communication skills, both written and verbal (including listening skills)
• Solid time management skills which include the ability to juggle multiple projects and meet critical deadlines.
• Excellent interpersonal skills to work in a team environment and to influence and interface with a broad range of stakeholders at all levels, both internal and external
• Proficiency in the Bank's desired competencies:
  • Collaborates: Building partnerships and working collaboratively with others to meet shared objectives.
  • Instills trust: Gaining the confidence and trust of others through honesty, integrity, and authenticity.
  • Communicates effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.
  • Values differences: Recognizing the value that different perspectives and cultures bring to an organization.
  • Customer focus: Building strong customer relationships and deliver customer-centric solutions.

SALARY RANGE: $160K - $175K

The Federal Home Loan Bank of San Francisco is committed to the principles of equal opportunity in employment (e.g., employees, applicants) and in contracting (e.g., suppliers, vendors) regardless of race, color, religion, sex, national origin, disability status, genetic information, age, sexual orientation, gender identity, status as a parent, or any other characteristic protected by law. We are committed to cultivating a workplace free of unlawful discrimination, harassment, and retaliation, and are dedicated to fostering vibrant communities by serving as a reliable source of liquidity and resources for affordable housing and economic development.

Salary ranges reflect the base salary that the Bank reasonably expects to pay for a given role and is not inclusive of annual incentive award opportunities, retirement benefits or the value of other health and welfare or other ancillary benefits. We consider many factors when determining base salaries such as individual background and experience, the competitive environment, education, particular skill set(s), and industry and institutional knowledge.

The Bank is committed to offering all team members challenging and engaging work with market competitive pay, retirement, and benefit offerings. In support of this commitment, the Bank routinely engages in market competitive benchmarking surveys and analysis to ensure our team members continue to be paid fairly and competitively.