MLOps is a really hot topic right now and there are many products out there that promise to meet all your needs to put ML algorithms in production. At the same time, many if not most ML projects still struggle to make it to production and teams have a hard time managing a large number … Continue reading In Search for the Holy Grail of MLOps: Taming the Beast of ML Use Cases →

FOR REASONS I’m reading a lot of startup literature right now, including Zero to Sold, The Mom Test, Four Steps to the Epiphany, and The Lean Startup. One thing all of these books have in common is that they say the old line of “build and they will come“ is wrong. Considering myself a technical … Continue reading A Plea for the Technical Founder →

I always felt that Data Science and Product Management share a lot of research aspects. When developing a new product, you have to work with assumptions, uncertainties, and gradually figure out a path to validate or verify these assumptions. You need to adapt till you have found something that solves a relevant problem for the … Continue reading What is Data Science/Product Fit And Why You Need It →

Running data science projects successfully is already quite challenging, and the first step is to hire some data scientists. Here are my answers to questions I often get asked.