01. About me
I was raised in Michigan for most of my life and even went to college at the University of Michigan to study computer science. After graduating, I moved to Chicago and worked at JPMorgan Chase as a software engineer. After a couple of years, I made the move to NYC and became a full-stack engineer at Capsule on the Partnerships team
02. Where I've worked
Capsule
2021 - Current
Software Engineer
- Led the development of a daily patient adherence calculator that aggregates prescription data across various healthcare partners and computes prescription compliance for over 50,000 patients
- Directed the back-end development efforts of Capsule’s Rx status bar by creating a microservice that subscribes to prescription status updates through an outbox pattern and allows customers to know real-time updates on their prescriptions
- Spearheaded the integration of AWS Canaries onto existing systems with high traffic to better monitor the health and latency of endpoints and web pages
- Modernized existing delivery workflow by automating status checks and reducing the need for manual discrepancy investigation on 17 percent of incoming orders
JPMorgan Chase & Co.
2019 - 2021
Software Engineer
- Prevented defects from getting introduced to the Chase website and mobile app by developing code that enhances the firm’s functional UI testing framework.
- Developed a web dashboard used by over 300 engineers to quickly review the results of their functional UI tests and identify areas of high risk
- Greatly reduced time spent on manual visual QA by automating the process using Applitools and streaming the resulting events to kafka and ElasticSearch to later be presented on the developer dashboard
- Modernized how developers prioritize testing by processing frequencies of over 1,000,000 customer journeys and visualizing the results on a D3 sankey diagram to identify popular pages
03. What I've built
Sales Analysis using Pandas
Jupyter notebook showcasing how you can carry out sales analysis using pandas.
Pandas Overview
Jupyter notebook outlining most of the important featurs and functionalities of the pandas library.
Path Visualization
React application that I created for people to better visualize and understand graph traversal algorithms like depth first search and breadth first search.
Deep Fashion
Full-stack application that uses deep learning to find cheaper,yet similar looking, alternatives to overpriced clothing.
Titanic Machine Learning From Disaster
Artificial neural network with the Keras framework to predict the survival outcome of passengers on the Titanic. Achieved an 80 percent accuracy, placing the algorithm in the top 7 percent of Kaggle competition submisttions.