Audit & Assurance Manager, Quantitative Credit Risk
- Evaluating ACL/CECL methodologies for consistency with ASC 326 (CECL) and U.S. GAAP and documenting conclusions.
- Reviewing and analyzing model code in SAS, Python, and/or R to assess implementation against model documentation and controls.
- Designing and executing data analytics using tools such as SAS, Python, R, SQL, Tableau, Power BI, and VBA to support audit objectives.
- Developing process improvements and tooling to increase efficiency through automation and standardization.
- Collaborating with audit engagement teams and presenting complex quantitative concepts to technical and non-technical stakeholders.
Required:
- Bachelor's degree in accounting, finance, information systems, statistics, business analytics, mathematics, economics, industrial and operations engineering, computer engineering, decision sciences, data science or related field.
- 6+ years of professional experience.
- 1+ years of experience managing and supervising teams.
- Experience in credit risk modeling, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD), including development and/or validation of credit loss models.
- Experience with financial modeling and valuation techniques.
- Active professional certification: CPA, CFA, FRM, PMP or related certification.
- You should reside within a commutable distance of your assigned office with the ability to commute daily, if required.
- You should expect to co-locate with team members or other colleagues in a Deloitte office, at a client site and/or virtually, based on specific team and business expectations.
- Ability to travel up to 10%, on average, based on the work you do and the clients and industries/sectors you serve.
- Limited immigration sponsorship may be available.
- Advanced degree in a quantitative discipline.
- Proficiency in SAS, Python, R, and/or SQL.
- Understanding of CECL approaches, including loss-rate/vintage, PD/LGD, migration/roll-rate, probability-weighted scenarios, and discounted cash flow (DCF) methods.
- Experience reviewing model performance evidence, including back-testing, benchmarking, sensitivity analyses, and outcomes analysis of ACL drivers.
- Knowledge of portfolio types under CECL, such as commercial and industrial (C&I), commercial real estate (CRE), consumer, residential mortgage, credit card, and auto.
- Experience with model risk management and evaluating third-party CECL solutions and vendor models.
- Experience working with large datasets and econometric models.
- Experience developing independent fair value estimates for financial instruments.
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