HSBC - AVP/Lead AVP/Senior AVP - Model Risk Management

Skills/Experience Required:

- Minimum 8 -12 years of experience of financial modelling experience in validation/development in Risk Management in Market Risk

- Master's degree in Mathematics/Statistics/Economic/Engineering/Computer Science/Management or any other quantitative fields of study

- Must have background in financial mathematics knowledge such as stochastic calculus, numerical methods, probability theory, regression, time series analysis

- Proficiency in SAS / R, Python, Matlab and MS Office tools like Excel & PowerPoint

- Proven expertise in using statistical algorithms for solving diverse business challenges and creating significant business value

- Candidate should have exposures in prepayment factor modeling with respect to conditional prepayment rate (CPR) forecasting techniques, Housing Turnover rate, Refinancing rate, LTV etc

- Candidate should have extensive model building experience utilizing various regression techniques and exposure to roll rate, delinquency, loss severity models and has covered sectors like RMBS, CMBS, US mortgage portfolios

- Experience working with panel data regression techniques and financial time series models, Monte-Carlo simulation techniques is required

- Candidate should have worked on Asset Liability Management models (Liquidity and IRRBB) including Net Interest Income (NII) modeling, Economic Value of Equity EVE modeling etc

- Candidate should have been involved in development of IRRBB NMD Deposit & Balance Sheet Modelling (static and dynamic) using Multiple Regression Model including Macro Economic Variables

- Candidate should have worked on modeling of Liquidity and Funding ratio analysis

- Candidate should have worked on transition of LIBOR-to-SOFR scenarios and analyzing the impact of cash flows/ payoffs

- Candidate should have worked in modeling of Structural Interest rate risk, Multi - Curve construction, OIS discounting and Earning at Risk

- Candidate should have strong understanding of various stress testing models such as CCAR/PRA and various other mandatory regulatory expectations for US such as OCC guidelines and OCC 11-7.

- Enthusiasm for proactively seeking, exploring and developing use cases for new data and/or tools/wider industry trends

- Candidate should be able to go through vast range of documentation and come up with concise set of questions highlighting model risk in the model.

- Strong business acumen with out-of-the box thinking to drive improved business performance

- Strong stakeholder management skills and seamless delivery of analytics initiatives across markets