This talk is part of the LEAD Seminar of March 6th. Check out the full program here »
How many Machine Learning opportunities are you missing out on because the overhead for model development, governance, deployment and operations is simply too high?
Today, proving the value of machine learning models is relatively simple. Yet, model development, governance and embedding model based solutions in our everyday systems and processes cost so much time, effort and money, that the threshold for building new machine learning solutions is very high. Hence we need an effective way to lower the threshold and reap the benefits of machine learning opportunities, while complying with all regulations and quality standards.
Although end-to-end teams and DevOps work extremely well to resolve bottlenecks in the development process, this doesn’t scale well. To make it scale, we need self-service platforms that support data consumption / production, model experimentation and model operations.
In this presentation Jurrit shares what bottlenecks they are facing today, what bottlenecks they want to remove
tomorrow and how they organize this transition.
My name is Jurrit de Vries, 42 years old and live just outside of Biezenmortel (a very small town between Tilburg and Den Bosch), with Charlotte and my 5 year old son Floris. We have an old farmhouse, which is a mandatory hobby, and so are some of the animals. Skiing is my non-mandatory hobby. Since 2019 I work at Rabobank as IT lead in Tribe Data & Analytics. In this position I am responsible/accountable for several IT squads and for the systems they build and run. It started out with a focus on Customer Data teams, shifting to azure data ingestion, running machine learning models, to building internal platforms for data scientists and analysts to do research, development and running machine learning in production. Before joining Rabobank I was a co-owner in a company focused on specialized webhosting, webdevelopment and linux administration.
My name is Stijn de Koning, I’m 41 years old, married and we have 3 young kids. Hence, I’m currently very passionate about sleeping. I have a software engineering background and joined Rabobank in 2022 as IT Lead Data Science. Together with many great colleagues I work on the transition towards end-to-end teams that combine the experimental value adding mindset from data scientists with the long term, high quality and maintainability mindset from DevOps engineers.