Model Development Role

Key Responsibilities:

- End-to-end development and governance and support of models in treasury/IRRBB space.

- End-to-end model development includes econometric forecasting models for key Balance sheet and income statement line items for capital and business planning purposes. This includes the calculation of Net Interest Income ("NII"), Non-Interest Revenue ("NIR"), Interest Rate Exposure ("IRE"), Economic Value Sensitivity ("EVS") , Funds Transfer Pricing ("FTP") and other associated interest rate risk metrics.

- Applies analytical thinking and knowledge of statistics / modeling / data analysis tools and methodologies.

- Model governance and support includes reviewing and timely submission of model documentations such as - Model development document (MDDs), Annual Model Review (AMRs), Ongoing Performance Assessment (OPAs), Model Change

- Addendum (MCAs), Limitation Record Change (LRCs) to Model Risk Management and other stakeholders.

- Develop and maintain a comprehensive modeling system that maintains consistent approach to data quality and modeling methods, audit, back test, tracking, annual validation which is critical in reducing the model operating risk

Qualifications and other Requirements:

- 4-6 years of relevant statistical modeling /econometrics experience and model development in financial domain.

- PG / Masters / PhD in quantitative discipline such as Statistics, Economics, Mathematics, or related discipline is preferred. Certifications such as FRM, CFA is a plus.

- Experience in development of models and metrics related to the Assets/Liability Management (ALM)/Interest rate Risk in Banking Book (IRRBB).

- Deep understanding of IRE, EVE/EVS and FTP concepts. Experience in behavioral modeling of non-defined maturity products is a plus.

- Extensive hands-on experience in developing econometric models and deep understanding of statistical techniques such as Linear Regression, Logistic Regression, Time Series, Panel Regression, Error Correction Models, Seemingly Unrelated regression and Cointegration.

- Extensive experience in programming and modeling using Python related packages (GitHub, DataFlame) is must. Working knowledge of statistical packages like SAS/R is a plus.

- Experience with SQL and databases.

- Domain knowledge and experience in PPNR, Fixed Income Securities, Mortgage Modeling, Deposit Modeling, Asset Liability Management, Interest Rate Risk, Capital Planning, etc.