Bricks and Mortar of a Data Science Product
November 19, 2019
A lot of companies are struggling with managing data science projects and get bogged into several unexpected difficulties. Newcomers on the data science field also face significant problems with hiring the specialists and organizing product teams efficiently. So, though, the data science is a well developed field, managing of data science projects is still quite challenging.
Nikita is Chief Data Officer in Russian Airline S7 with over 100 planes in fleet. Three years ago the airline company launched the first data science projects with only two data science project managers involved. Now they have a team of around 40 specialists in the fields of product management, data engineering, data science, software development and business analysis. Over these three years they have successfully implemented a few state-of-the-art machine learning products in some core areas of their business.
Nikita believes that their experience and ideas can help you and your organizations to launch and operate data science teams more effectively. In his talk he is going to cover the following areas of a data science management: roles and competences, organizational structure, product management frameworks, use of the Data Lake, Data Catalogue and Data-as-a-Service, discovery of new business cases and many other.