look around
capgemini
At Capgemini, I helped create an AI-powered resume screening system, which cut manual review time by 20 hours weekly. I developed algorithms that achieved a 95% accuracy rate in matching candidates to jobs, making our recruitment process much better. I also led a team of five in an Agile setup, finishing the project two weeks early and 15% under budget. Plus, I presented our results to the C-suite, securing their approval to expand the project further.
scope
I spent the summer of 2023 working as a frontend software engineer at Scope in Los Angeles. My main project was setting up connections to pull in financial data, which made everything flow more smoothly. I wrote plenty of tests to catch bugs early, which meant way fewer issues down the line. I also teamed up with QA to make sure everything was solid, and we ended up cutting post-release problems by 20%. Plus, I ran product demos every couple of weeks for the team, collecting feedback that helped shape our next steps.
NYU
During the summer of 2022, I worked as a research assistant at NYU Abu Dhabi. I dove into data from over 25 research papers, uncovering insights that helped guide some data-driven decisions. I also improved our research simulations by using containerization, which boosted computational efficiency by 30%. On top of that, I created SQL procedures to better organize and analyze raw data, which cut down our processing time by 20%.
Bloomberg
In Spring 2024, I worked on a project at Bloomberg Tech Lab in Los Angeles, where I designed and built a system to handle real-time market data updates using a producer/consumer model. I developed specs for a reliable data transfer setup capable of managing complex financial instruments and worked closely with engineers to fine-tune the system architecture to meet the demands of high-frequency trading.
Kaggle Credit Risk Classification
In Spring 2024, I led a project for a Kaggle case competition focused on credit risk classification, where we ended up placing 2nd. I used data analysis to help reduce default rates by 15%, keeping in line with risk management strategies. By implementing gradient boosting, we improved classification accuracy by 20%, which really boosted our financial modeling. I also designed three credit card risk models that incorporated debt management and portfolio analysis, lowering risk exposure by 35%. To top it off, I fine-tuned and cross-validated our models, reaching an 85% precision rate.
moviefy
In the 2023 academic year, I created MovieFy, a platform built with Java, where I integrated MySQL for database management and used RESTful APIs to deliver content smoothly. I handled the back-end functionality, API calls, and data processing, which cut loading time by 25%. I also developed interactive UI components in TypeScript, making the platform more user-friendly and increasing session times by 30%.