May 2023 – Jul 2023 · 2 mos · University of Windsor, Canada · On-site

• Developed a portfolio strategy focused on tail-risk diversification, engineering features and estimators that reduced downside vulnerability in stress scenarios. The approach improved out-of-sample risk-adjusted performance and demonstrated materially lower portfolio drawdown risk.

Dec 2022 – May 2023 · 5 mos

• Designed and validated statistically grounded trading signals that fed the firm’s alpha-generation pipeline. My work combined rigorous backtesting and signal refinement to produce repeatable, production-ready research contributions.

Oct 2022 – Dec 2022 · 2 mos · Remote

• Delivered NLP solutions to extract actionable insights from customer feedback, surfacing themes that directly informed product and marketing decisions. The analysis led to measurable improvements in campaign targeting and ROI.

Jul 2022 – Oct 2022 · 3 mos · Remote

• Pioneered an adaptive, nonparametric estimation framework that improved predictive fidelity in low-signal financial datasets. The method outperformed standard parametric models in capturing tail behavior and structural breaks, enabling stronger risk assessments.

May 2022 – Jul 2022 · 2 mos · Bengaluru, Karnataka, India

• Built and validated machine-learning-driven investment models and diversified pairs strategies, applying rigorous validation and performance metrics to capture market opportunities. The strategies were implemented with disciplined risk controls and delivered strong realized performance.

May 2021 – Nov 2021 · 6 mos

• As a founding engineer to design and launch the startup’s core web platform, driving product vision into an operational digital experience. Contributed end-to-end across product, engineering, and launch operations to get the platform production-ready.