DataOps Polska - The way from PoC to an automated model factory.

"The way from PoC to an automated model factory. Challenges in the work of the Data Science team in a large organization."

I've been analysing data for over twenty years.

I worked as the only one Data Scientist in an organization and was a member of larger teams. I built Data Science teams from scratch. I manage teams of Data Scientists, data engineers and Machine Learning engineers.

I had the privilege of working in organizations of very different sizes. From the start up right after series A stage to the sixth in the world telecom.

In each of these organizations, regardless of their size, management method or dependence between teams, there occurs a repetitive group of challenges. I would like to talk about them. Some of them are obvious. Some quite surprising. Most of them are easily overlooked.

I would like to tell you about three basic groups of problems you encounter when you are going to start a project in the field of Dart Science. And why not Data Scientists are often the most important people in such projects.

I will tell what good and bad things to people living Data Science have been made by on-line courses at Coursera and Udemy.

I would like to devote the most time to the issue of what to consider when defining PoC and when moving from the PoC phase to the production implementation phase.

About speaker:

Radosław Kita Head of Data Science in Ringier Axel Springer Polska.

He works for many organizations: from the startup phase to highly developed holdings. He built and managed several teams dealing with Data Science. He has carried out several dozen projects in the area of using machine learning methods. Some have failed. Some have brought quite a lot of money.

On a daily basis, he builds content recommendation systems, dynamic retargeting models, cross and up selling, anti-churn or anti-fraud systems. The craziest projects in which he participated: calculating the risk of granting credit for people without a banking history based on the way the Internet is used, identifying people using different SIM cards.

He worked for: Onet.pl, TVN, Alior Bank, Allegro, Veon, Adform.