The Federal Home Loan Bank of Chicago-posted 3 months ago
$75,325 - $125,500/Yr
Full-time • Entry Level
Chicago, IL
251-500 employees
Credit Intermediation and Related Activities

The FHLB is a leading provider of credit solutions, committed to delivering exceptional service and innovative products to our Members. As part of our dynamic team, you will have the opportunity to contribute to the development of risk rating models and play a vital role in shaping our strategies for managing credit risk. We are seeking a quantitatively strong Risk Analyst to build and maintain credit risk models and perform credit analysis for depository members (banks and credit unions), with additional exposure to insurance counterparties. The ideal candidate brings rigorous statistical training (e.g., econometrics, probability, time-series) applied to credit risk, strong R programming, and hands-on financial statement analysis. You will use Databricks and SQL to work with larger datasets, and collaborate with Sales Directors to recommend credit structures and terms aligned with our risk appetite. This is a hands-on role for someone who enjoys model development, statistical analysis, and underwriting judgment.

  • Develop and maintain advanced credit risk models using statistical and econometric techniques to assess member risk profiles, including banks, credit unions, and insurance companies.
  • Design, implement, and enhance models in R (and/or Python) for credit risk measurement, stress testing, benchmarking, and scenario analysis, ensuring compliance with regulatory and internal standards.
  • Leverage Databricks and other cloud-based platforms to process and analyze large-scale financial datasets efficiently, integrating structured and unstructured data sources.
  • Perform data mining, statistical analysis, and predictive modeling to identify trends, correlations, and emerging risks within member portfolios.
  • Automate recurring analytics and controls (e.g., score recalcs, risk rating refreshes, sensitivity checks) using R, SQL, and VBA where appropriate.
  • Conduct statistical analysis and portfolio diagnostics (trend analysis, correlations, concentration, PD inputs where applicable).
  • Develop clear visualizations and dashboards to communicate model insights and portfolio risk to senior stakeholders.
  • Monitor model performance and drift; propose recalibration or redevelopment based on statistical evidence and business need.
  • Stay current on credit risk modeling practices and regulatory expectations relevant to depository institutions.
  • Perform credit analysis and risk ratings for depository members, including quarterly reviews and ongoing monitoring of financial condition and liquidity/funding profiles.
  • Analyze and recommend approval for new and/or continuing borrowers, aligned with credit policy and risk appetite.
  • Recommend credit and collateral terms for banks and credit unions, incorporating appropriate structures and risk mitigants.
  • Partner with Relationship Managers and borrowers to structure transactions and address risk considerations.
  • Develop, refine, and support credit underwriting standards for depository institutions to ensure consistency and regulatory alignment.
  • Monitor macroeconomic and regulatory developments and assess their impact on member creditworthiness.
  • Prepare and deliver reports and presentations to senior management, regulators, and the Credit Committee.
  • Contribute to credit risk policy updates and cross-functional strategic projects.
  • Identify and implement process improvements to reduce manual work and enhance control and efficiency.
  • Bachelor's or Master's degree in Mathematics, Statistics, Quantitative Finance, Econometrics, or a closely related analytical field.
  • 1-4 years of experience in credit risk analysis, banking, fixed-income, or institutional underwriting.
  • Demonstrated foundation in statistical modeling, probability, and quantitative methods applied to credit risk.
  • Familiarity with regulatory filings, GAAP, and financial statement analysis for financial institutions.
  • Experience with financial data platforms such as S&P Capital IQ / SNL, Bloomberg, or similar.
  • Advanced quantitative/statistical skills with the ability to build, interpret, and explain credit risk models.
  • Proficiency in R for statistical modeling and analytics; experience with SQL and Databricks for large-scale data processing is a plus.
  • Knowledge of U.S. banking industry dynamics, credit risk principles, and regulatory environment for depository institutions.
  • Strong Excel (including advanced functions; VBA a plus); familiarity with Tableau and Bloomberg helpful.
  • Excellent written and verbal communication skills, with the ability to distill complex analyses for non-technical audiences.
  • High attention to detail, intellectual curiosity, and sound judgment.
  • Effective time management; comfortable working both independently and within a team environment.
  • Collaborative, in-office operating model
  • Retirement program (401k and Pension)
  • Medical, dental and vision insurance
  • Lifestyle Spending Account
  • Competitive PTO plan
  • 11 paid holidays per year
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