Join Deloitte’s Audit & Assurance Valuation and Analytics team to support audit objectives through financial instrument pricing, valuation analysis, and data analytics. In this role, you will work with market data, valuation tools, and audit teams across industries to help assess complex instruments and document technical analyses. This opportunity offers exposure to valuation methodologies, structured products, and cross-functional collaboration in a dynamic professional environment.
Work you'll do
As an Assistant, Valuation and Analytics Advisory in the Valuation and Analytics team, you will be responsible for:
- 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.
- Contribute to AI risk and governance processes, including model documentation, control design, validation support, testing protocols, and ongoing monitoring.
Location: Bangalore & Gurugram
Shift Timings: 11 AM to 8 PMNight shifts may be needed during January and February.Qualifications
• Mandatory: Bachelor’s degree in mathematics or Statistics, or B.E./B.Tech. in Computer Science Engineering.
• Preferred certifications: CFA, FRM
Required
• 2-4 years 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.
• 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.
• Proficiency in SAS, Python, R, and/or SQL.
• Strong understanding of the design, development, testing, and deployment support of AI/ML solutions, including Generative AI, LLMs, and traditional machine learning models.
• Experience with LLM prompt engineering, fine-tuning, and RAG (Retrieval Augmented Generation) architecture.
• Strong presentation, communication, client management, project execution and mentoring skills required.