How UBS Improved Efficiency and Productivity across the Data Science Lifecycle

Session sponsored by Domino Data Lab

Enterprise MLOps platforms are a critical component in a company’s journey to become model-driven. In this presentation, data science leads from Swiss bank UBS will share their story about the challenges that led them to look for a centralized and scalable solution for data science. They’ll also share the reasons behind their selection of Domino as their Enterprise MLOps platform, the results they have already achieved, and their plans for new data science use cases.


Andreas Heinzerling, Enterprise Account Executive @ Domino Data Lab

Andreas has a Master in Business Administration and more than 10 years of experience in Enterprise Software. He and his colleagues help large companies in the Pharma, Insurance, Banking, and Manufacturing industry to improve their Data Science outcomes by getting models into production faster, promoting collaboration, ensuring reproducibility of model results and automating model monitoring.

Anton Olshevsky, Data Science Platform Lead @ UBS

Anton is a seasoned business transformation professional with 15+ years of industry expertise. Throughout his career he worked for top technology, consulting and financial institutions as project manager, advisor and architect. Recent years he drives implementation and transformation initiatives within risk organisation in the bank, covering all aspects of model development, validation and execution.

Ilhami Goerguen, IT Product Head for Data Science & Model Services @ UBS