Company Overview
RedOwl's software-as-a-service analyzes the massive digital trail created by the modern firm, generating valuable insights from enormous quantities of data presented in intuitive dashboards. For some of the largest financial institutions in the world, we ingested live streams of all of their trading data (corporate and personal), email archives, instant messages, etc, to look for patterns of socially damaging (and illegal) behavior such as insider trading. Named Most Innovative Company of the Year at the 30,000-person RSA Conference 2014.
I worked for RedOwl’s Baltimore headquarters as we grew the startup, built our analytics platform, and raised roughly $25 million. Several years after my departure the company was sold to ForcePoint in a successful exit.
Technical Work
I designed, prototyped, and implemented new statistical methods and visualizations for RedOwl. I was what you might call a “full stack” data scientist—I wrote Java and JavaScript to build the ETL, services layer, and front end for our statistical software, and I used the scripting language R for one-off projects. For our front end, we used an Ember.js framework written in CoffeeScript, with D3.js for most visualizations. Our algorithms focused on anomaly detection, finding unusual patterns that differ from baseline behavior. We used existing machine learning algorithms while also developing our own outlier detection techniques.
As the team lead for a team of engineers, I supervised our sprint planning process, delegating tasks and empowering a collaborative approach to problem solving.
Client Engagements
As a technical lead, I led extremely successful client engagements with top financial, legal, and energy firms. My clients purchased the software, invested in the company, and, where applicable, recommended us to firms that they owned. I also served as the analytical lead at meetings with VCs and advisors during the Series A raise.
