Keith Woon

I major in Data Analytics and aim to apply my skills in the financial industry. What differentiates me is a blend of quantitative modelling capability and commercial intuition. I am an entrepreneur and have worked with the sales team since I was 18, so I want to bring this combination to the trading desk. I want to take my first step into the finance world with a technology background. 

Across my internships and ventures, I gained strong analytical and commercial experience. As a Commercial Analyst at Wilmar, I built ARIMAX models for over 200 commodity-linked SKUs, improved forecasting accuracy by 12% and stability by 30%, developed pricing ladders and category indexes that contributed to 4–6% YoY profit growth, automated VBA pricing workflows, and processed 100k+ API records to build Power BI dashboards for revenue and customer insights. At UOB, I supported high-volume payment operations by cleaning large datasets, monitoring AS400 and Control-M batch jobs, resolving system issues, and coordinating with vendors and internal teams on project deliverables. Beyond corporate roles, I scaled two e-commerce ventures generating ~$2,000/month, negotiated directly with Chinese suppliers, operated a co-living business that achieved 100% occupancy within one month while raising $90k in private loans, and automated financial tracking systems to reduce administrative work by 40%.

Through my academic and trading-related projects, I built a strong foundation in derivatives, portfolio hedging, and equity analysis. In the MSCI Bangladesh Futures Hedging project, I developed hedge strategies for a $100M equity portfolio using Eurex-traded MSCI futures, implemented naïve and OLS-optimal hedge ratios, analysed liquidity, correlation, and basis risk, and evaluated variance reduction to identify the most effective hedge instrument, supported by Python-based data cleaning and regression testing. In my Option Pricing Models project, I built Monte Carlo, Binomial Tree, Black-Scholes, and Put-Call Parity pricing engines, running 1k–100k simulations to reduce pricing error from 5% to under 1%, validating convergence through put-call parity and documenting all model behaviour through tables and figures. As Team Lead for the SUTD-CFA and Investment Science stock pitch projects, I prepared full equity research reports—covering financial statements, DCF valuation, key metrics, and risk assessment—and delivered pitches to faculty and industry judges, demonstrating my ability to communicate complex financial analysis to non-technical audiences.