- Knowledge in Current Expected Credit Losses (CECL) loan loss reserving process, loss forecasting, probability of default and risk rating development. Ensure that credit risk models and analytics address both internal and regulatory requirements, such as Stress Testing and Allowance for Credit Loss accounting standards.
- Lead team members in developing and implementing predictive analyses and models, visual/interactive reporting, segmentation analysis, and process automation. Identify the problem, provide potential solutions, and design the analysis or model construct.
- Present findings and follow-up with business partners and executive management to ensure results are implemented.
- Develop processes for analytic support and pricing for bank acquisitions and loan pool purchases.
- Provide analytical insights to the executive management and board of directors on credit trends, including root cause analysis and potential solutions.
- Modeling data for automation rules in underwriting systems and portfolio management actions
- Strong quantitative and analytic skills, knowledge of statistical software, and problem-solving ability are a must.
- 4-10 years of progressive, related experience.
- MA/MS in Statistics or Quantitative field strongly preferred.
- CECL reserving methodology experience preferred
- Strong SAS programming skills, including SAS macro-language, and
- SAS/Stat, SAS Enterprise Miner, and/or R/Python preferred.
- Background experience and knowledge with SQL
- 2+ years of Statistical Modeling experience
- Experience with Moody's ImpairementStudio is beneficial.
- 2+ years prior Banking or Financial Services Experience Preferred
Keywords: Credit Risk, Data Mining, Statistical Modeling, CECL, CCAR, SQL, SAS, R, Python