- Leading data science efforts on developing omni-channel ML models for LTO decisioning and fraud detection. Improving portfolio funding volume while reducing charge offs.- Support and validate credit policy score cards.- Working with major credit bureaus to evaluate new data products to improve AI/ML models' predictive power.- Initiated ML modeling efforts for direct mail channels of customers re-engagement and prospects conversions.- Collaborate with internal/external auditing bodies to pass model validation and compliance reviews.- Recruit and maintain a team of data scientists that provide services to internal and external clients.

- Leading a team of quantitative analysts to develop risk based pricing model for secured and unsecured loan.- Develop roll rate model to forecast loan loss for CECL reporting.- 3 lines of model validation efforts.

- Developed and maintained underwriting models for personal loans in sub-prime space, both secured and un-secured.- Developed risk based loan pricing model to properly incorporate PD/LGD, and comply with pertinent regulations, e.g., Reg Z.- Leading data science efforts to develop prospecting models for direct mail acquisition channel. Pre-screen model score cards includes propensity and credit quality.- Recruited and trained/developed junior data scientist.

- Market and credit risks analysis for margin trading accounts.- Monte Carlo simulation based portfolio value analysis and risk assessments.

- Develop lending decision models to evaluate default probability and loss given default for online loan portfolio.- Develop collection model to forecast ACH payment risk and collection losses.

- Commodity (power/gas) derivatives pricing/structuring/risk evaluation.- Stress test under DFAST framework.- Monte Carlo based counterparty credit risk (CVA).