January was founded to address one of the thorniest areas of consumer finance. Jake Cahan's thesis was straightforward: better technology leads to a more effective AND more human approach to debt collection. But building a team that can execute isn't easy.
When I’m asked about January’s differentiation, I start by describing the infrastructure beneath our collections strategy and my coworkers that built it. Our platform collects and unifies previously fragmented data to power machine learning models that personalize every consumer interaction across channel, content, timing, and offer. We've built the infrastructure to take those models from idea to experiment to production, and keep them improving over time. That's known as MLOps, and it's what enables good outcomes to compound for our clients and their consumers.
Now, January’s infrastructure is being recognized alongside some of the biggest names in tech. In June, my colleague Thomas Brink is speaking at Snowflake's Summit — one of the largest data and AI conferences in the world — on how January has built MLOps best practices inside the Snowflake environment with machine learning projects from experimentation to deployment.
Speaker selection was highly competitive, and Snowflake flagged us as one of the most sophisticated early adopters of their platform. Here's the session: https://lnkd.in/etPSraeQ
Shoutout to Christine Commeignes and Gerhard Nordemann for their early work building our analytics infrastructure to get us to where we are today!
If you want to work alongside impressive people like these, we're always hiring!
Congrats! Well deserved! Thanks for the great partnership 🙌