Quant Strategist
Cross‑asset quant/data scientist with experience across commodities, rates, FX, and credit. Expertise in derivatives pricing, price curve modeling, volatility modeling, forecasting, macro‑factor research, risk models and ML/AI for trading and risk. Developed and validated models across structured products in FICC & options, IR exposures, PD/LGD, and cross‑asset VaR. Combines macro‑quant rigor with modern ML workflows to support trading, structuring, and risk.
Technical:
Python (9 yrs): Pandas, Numpy, Statsmodels, Arch, Scikit‑learn, XGBoost, LightGBM, Cvxpy, Scipy, Pmdarima,
Quantlib, SqlAlchemy, Matplotlib/Seaborn, Plotly etc.
Databricks, Snowflake, Azure, PySpark, PyTorch, Tensorflow, GitHub
SQL (9 yrs); Matlab & VBA (8 yrs); R (2 yrs); SAS (4 yrs); C++/ C# (3 yrs)
Cross Asset Quant Experience:
--Derivatives pricing/Greeks & model development and validation across FX, fixed income, equities, and commodities, including structured products and exotic options; cross‑asset risk models (FSA/BoE, others)
--Interest‑rate exposure modeling, futures analytics, curve‑risk decomposition supporting IR derivatives, macro‑hedging, and risk‑management workflows; MBS, bonds, IR swaps (CMHC)
--Multi-factor forward curve models (HJM), forward‑curve construction and shaping‑factor modeling across multi‑tenor and cross‑asset term structures, supporting trading, structuring, and valuation
--Advanced stochastic modeling for asset prices including jump‑diffusion, mean‑reversion, volatility‑surface calibration, Monte Carlo simulation, and dynamic programming for structured products
--Macro‑factor modeling, PD/LGD analytics, and systemic‑risk research, integrating econometric factor models, PCA, and macroeconomic variables for stress testing and scenario design (FSA/BoE, CMHC)
--Machine learning models applied to pricing, risk and forecasting
Work Experience:
Quantitative, Market & Credit Risk; Derivatives Valuation & Greeks, Quantitative Research /Trading
Global Macro Analysis/Trading; Model Development/Validation; Forecasting; Stress Testing
Time Series Analysis, Econometrics, Machine Learning/AI; Factor Models, PCA; Volatilities Models
Dynamic Programming; Optimization; Monte Carlo Simulations; Stochastic Calculus, Binomial Trees
ODEs & PDEs; Numerical Methods; Probability, Statistics, Measure Theory, Linear Algebra, Multiv. Calculus,
Real Analysis, Optimal Control; AI Automation and Integration: Agentic AI systems, LLM