Gabriel talks to us about the difficulties of scaling ML products across an organization. He speaks about differences in profiles of data consumers and data producers, and the challenges of educating engineers so they have greater insights into the effects that their changes to the system may have.
In this episode
Chief Data Officer, Ocado Technology
Gabriel joined Ocado Technology in 2020 as Chief Data Officer, bringing over 10 years of experience in leading data science teams and helping organizations realize the value of their data. At Ocado Technology his role is to help the organization take advantage of data and machine learning so that we can best serve our retail partners and their customers. Gabriel is a guest lecturer at London Business School and an Honorary Senior Research Associate at UCL. He has also advised start-ups and VCs on data and machine learning strategies. Before joining Ocado, Gabriel was previously Head of Data Science at the BBC, Data Director at notonthehighstreet.com, and Head of Data Science at Tesco. Gabriel has a MA in Mathematics from Cambridge and an MBA from London Business School.
Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.