Credit Risk Analytics Analyst

About the role

Reporting to the Manager, Enterprise Risk Analytics, the Credit Risk Analytics Analyst is part of the Enterprise Risk Analytics team, a dynamic group of professionals responsible for producing valuable recurring risk reporting and analytics, as well as advancing the modeling framework to identify and manage financial risk. This role combines quantitative, modeling, communication, and technical reporting skills to enhance credit risk modeling, monitoring, and reporting capabilities.

Responsibilities

• Own third-party vendor credit loss models for CRE and C&I, including periodic analytical review of model performance, updates, and maintaining internal model documentation consistent with internal and regulatory expectations.
• Become a leading expert in Moody’s CMM, RiskCalc, MPA, and ZMDesk models, including periodic review of model performance, updates, and developing deep knowledge of model mechanics.
• Advance and refine the use of Moody’s models by leveraging external and internal data to improve credit risk accuracy and support stress testing, credit risk attribution, credit VaR, sensitivity analysis, and risk decomposition initiatives.
• Lead contributions to quarterly and annual end-to-end stress testing exercises, conduct ad-hoc analysis, and develop meaningful stress scenarios for management.
• Contribute to integrating risk results into capital planning, budgeting, and risk appetite frameworks.
• Generate periodic reporting on financial risks using Tableau dashboards, Microsoft Excel, PowerPoint, and Word for both recurring and ad-hoc needs.
• Drive automation of modeling routines and report/dashboard generation to ensure consistency, accuracy, and repeatability in credit risk reporting.
• Contribute to the design and implementation of risk reporting across various media.
• Collaborate with data and technology teams to improve data infrastructure supporting risk analytics initiatives.
• Adhere to applicable federal and state laws, regulations, and guidance, including anti-money laundering (e.g., Bank Secrecy Act, US PATRIOT Act).
• Comply with Bank policies and procedures, complete required training, and identify/report suspicious activity.

Requirements

• Degree in a quantitative discipline (e.g., Statistics, Finance, Mathematics, Engineering, Economics) required; advanced degree (PhD or MSc in a STEM discipline or Economics/Finance) preferred.
• 2+ years of experience in financial services (banking, asset management, insurance) with direct exposure to analytics and modeling applied to credit risk and/or market risk.
• Experience with programming languages, particularly Python.
• Experience utilizing and merging data from a variety of databases.
• Experience with financial modeling techniques, including credit losses, loss migration, interest rates, volatility, derivatives, VaR, prepayments, capital, forecast techniques, stress testing, scenario analysis, sensitivity analysis, RAROC, liquidity, and FTP.
• Prior experience in credit risk reporting and working with databases.
• Prior experience automating tasks.

Skills

• Deep understanding of credit risk models (PD, LGD, Credit VaR, etc.) and ability to provide expert insight into credit risk results.
• Excellent communication skills (visual, verbal, and written) with the ability to articulate complex concepts to diverse audiences.
• Proficiency in generating reports using Tableau.
• Proficiency with quantitative modeling techniques (regression, simulation, optimization).
• Strong interpersonal skills to collaborate across divisions.
• Ability to work under pressure, meet deadlines, manage competing initiatives, and adapt to a fast-paced environment with a focus on accuracy and detail.
• Knowledge of the latest modeling developments and trends.

Certifications such as CFA, PRM, or FRM are a plus. Candidates residing within BankUnited's footprint may be given preference.