● Collaborated in a small, like-minded team with passion for quantitative finance, with meticulous attention to detail.● Designed a low-frequency trading strategy using time series analysis to forecast weather impacts on commodities markets, optimizing risk-adjusted returns using Monte Carlo simulations.● Developed strategic goals to guide the group's research focus, ensuring alignment with industry trends.

● Led center-wide operations as the primary contact, implementing a Power BI-based request management system adopted across the JSC, resulting in streamlined team communications and significant cost savings of $200,000+.● Crafted and executed plans for the conference room optimization project, enabling swift on-time completion of three high-priority projects and improving resource allocation while reducing scheduling conflicts by 26%.● Collaborated with cross-functional teams to integrate the Geographic Information System and Space Utilization Tool, accurately updating the NASA database in a fast-paced environment.

● Developed a program to download and process 3TB+ of big data from satellites, utilizing MySQL, AWS S3 buckets, then parallel processing to predict NO2 levels on the surface from tropospheric data (Pandas, NumPy).● Implemented Purged K-Folds cross-validation to effectively mitigate time series data leakage, enhancing the integrity of model training and testing phases.● Engineered a machine learning program using Elastic net regression and LightGBM, achieving an R² of 0.401 and enhancing it to 0.470 with a neural network ensemble (PyTorch).

● Grew a club representing minorities in STEM into a global organization with 60+ members, raising $300,000+ in sponsorships and hosting international hackathons with 1,400+ participants from 50+ countries.● Cultivated a collaborative, growth-focused environment through clear communication and continuous learning.● Managed budgets and delegated work, assisted with conflict resolution and collaboration between divisions.

● Analyzed real-time market data using Bloomberg Terminal and Excel to identify trading signals and adjust forecasts, optimizing trading strategies during volatile market events.● Developed DCF models and conducted P/E ratio analysis for equities in the hospitality industry, leveraging time series data to support trading decisions and achieve a 94% accuracy rate in earnings predictions.● Conducted EPS estimation during the COVID-19 pandemic using statistical analysis, providing quantitative insights that strengthened investment strategies.● Collaborated with the compliance team, ensuring 100% adherence to regulatory reporting and financial standards, which minimized compliance risk and maintained the firm’s reputation with regulatory bodies.