Assisting in the development of machine learning models that analyze 250+ fundamental and technical factors to predict stock price movements and confidence levels for S&P 500 equities, using over 30 years of historical data. Working full-stack to enhance both front-end UI/UX and back-end architecture, optimizing speed and reliability for customers. Leveraging Python, Pandas, and PyTorch to build, train, and optimize predictive models, while implementing robust backend systems to improve overall performance and user experience.

Tech4Refugees&Immigrants is a non-profit organization dedicated to improving the accessibility of social services for immigrants and refugees in Seattle, recognizing the challenges posed by language barriers and complex social services websites. In my role, I led a team of four engineers in collaboration with the founder, guiding the company from ideation to a viable product that served as a proof of concept to secure funding. We crafted comprehensive project objectives, technical requirements, and user flows, consolidating these requirements into a prioritized backlog based on technical complexity and business value, structured within an Agile Scrum sprint timeline. To measure success, I created a business review metrics sheet with Key Performance Indicators (KPIs) to track the success of our deployments and quantifiably prove that our efforts increased accessibility and engagement. Through this project, I gained skills in Flutter, Google Firebase, Automated Email Service API, and Web Crawling API.

Worked for Roster, in AWS FinTech. Led initiatives to identify product improvements, focusing on cost reduction for the rapidly scaling product. Dove deep into customer and developer conversations to understand pain points and expectations, forming the foundation for solution development. Collaborated with Product, Program, and UI/UX teams to assess and implement potential improvements.

I found the product-market fit for "Second Opinion," a tool powered by ML model, Crystal Ball, designed to boost investor confidence in their trading decisions. To achieve this, I gamified a test to gather feedback from potential consumers, identifying their preferences and the features they desired from Crystal Ball. Additionally, I conducted tests to compare the accuracy of Crystal Ball against various levels of stock analysts, which helped validate its effectiveness. I also explored the pricing strategy by determining the amount potential consumers were willing to pay for the tool. Understanding consumer reservations was crucial, so I delved into their concerns to enhance the product’s appeal and functionality. The entire project was developed using ReactJS and MaterialUI, ensuring a modern and responsive user interface.

Created a website for Stock Leaders, a list compiled of stocks that outperform their sectors and are projected to go up in price. Created a paid subscription newsletter for customers, using Material UI and ReactJS, that replaced a static email sent out daily with a dynamic webpage. Newsletter webpage displayed: Highest Performing Sector, Industry Names, Stocks Falling Below Criteria, First Pick, Date, Recent Pick Date, Return Since Picked, and Charts.