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whoislewys®

About

I've been deeply interested in technology from a young age. My dad had a side hustle of fixing computers for people - seeing computer parts all over the floor and running ipconfig in a Windows XP terminal piqued my interest.

In middle school, I jailbroke iPods and sold them to kids in middle school, but I didn't start coding till my last year of high school.

I failed the AP Computer Science exam, started actually learning to build software a semester before college, and haven't stopped since.

Work

Sana Benefits

Senior Full Stack Developer

Jul 2022 - Mar 2023

At Sana, I was part of the SanaMD team, a team focused on integrating Sana's proprietary insurance technology into a company-owned healthcare clinic.

Dovly

Mobile Tech Lead

Aug 2021 - Apr 2022

As the first React Native hire, I shepherded the mobile app from private beta to public launch on the Google Play & Apple App Stores, leading to over 50,000 downloads and an average rating of 4.8 stars with over 7000 reviews. The app increases users' credit scores with several secret techniques. Sexy, right? ...Can credit scores be sexy?

Workiva

Full Stack Software Developer

Jan 2019 - Jul 2021

I worked as a Full-Stack Developer at Workiva, whose collaborative compliance software is used by 80% of the Fortune 500. My first focus (as an intern) was refactoring the document attachment functionality from the original monolithic system into a separate microservice. This Java microservice had greater than 80% coverage with JUnit, included a MySQL database with a schema I helped design, and was deployed using Rancher and Helm on Amazon EKS. The frontend was written in React & Dart. My first experience working in a large organization, developing a large distributed system, and digging through Splunk on support rotation. I have extremely fond memories of my team and time here :)

Mood Industries

Technical Co-Founder

Feb 2017 - May 2020

My first serious bit of programming. Built an iOS & Android music streaming app with React Native & Redux (15,000 WAU). Scraped a bunch of songs to assemble a dataset of music categrized by mood. Used deep learning to train a novel music recommendation model & deployed it on Google Cloud. Set up in-depth event analytics and tracked progress with Amplitude. Also built a bunch of functionality using Rails.

Projects

TODO...