Professional Summary
Quantitative risk specialist with 20+ years of experience in financial derivatives, risk modeling, and data analytics.
Proven expertise in developing and validating risk models across multiple asset classes, leading technical teams,
and delivering client-focused solutions. Adept at Python, VBA, and cloud-based platforms with a passion for
optimization and innovation. Strong background in both buy-side and sell-side environments with regulatory
compliance experience (MAS, BNM, Basel).
Professional Experience
- Provided SA-CCR implementation guidance across multiple asset classes
- Optimized Dupire PDE Local Volatility surface building in Python for VaR-testing engine
- Optimized Autocallable contract valuation in Python
- Developed accelerated Monte Carlo frameworks for derivative pricing
- Provided implementation guidance on IRRBB pre-payment modeling
Technologies: Python, Excel VBA
- Directed pre/post-sales for AxiomaRisk and Performance Attribution solutions
- Conducted buy-side client demos across multi-asset classes (EQ, FX, FI, ESG, Crypto, Private Assets)
- Developed Python automation scripts using AxiomaRisk API, reducing report generation time by 70%
- Created Excel integration tools using XLWings for real-time market data access
- Collaborated with engineering teams to resolve complex client technical issues
Technologies: Python, Pandas, Jira, Salesforce, AxiomaRisk API, Postman
- Designed Monte Carlo+bootstrap models for Operational Risk capital allocation
- Implemented Gaussian & T-copulae for tail-risk aggregation and Euler Allocation to quantify risk across 8 business units
- Built COVID-19 R₀ prediction model using polynomial regression (92% accuracy)
- Built FFT-based convolution tools for joint distribution modeling
- Developed Python based custom distribution (multi-modal) distribution fitting tools
Technologies: Python, Excel VBA, SQL
- Led regional 5-member team validating traded/non-traded portfolio value and risk
- Presented validation results to senior management and regulators (BNM, MAS, HKMA)
- Developed independent pricing validation tools for FXO, IRO, Equity Derivatives
- Authored model documentation standards adopted bank-wide
- Designed IRRBB framework for non-maturing assets/liabilities
Technologies: Python, Excel VBA, C++, R, Matlab, MySQL
- Developed benchmark pricing models for derivatives across FX, EQ, IR asset classes
- Created volatility surface generators and correlation modeling tools
- Mentored junior team members on quantitative techniques
- Developed staging tools for reading XML based formulae into C# proprietary software for Credit Risk
- Implemented logistic regression based tools for PD
- Developed Asian Basket option pricing and greek models for the market risk department
- Developed spark spread and crack spread pricers in VBA & C++ for the Middle Office
- Worked with Murex to incorporate Energy Derivatives into the risk engine
- Developed Winter method based hourly profiling tool in SAS to capture hourly power profiles