Lessons from the deep end of data science

Data science and AI promise to revolutionize the world, but how do you do this in a company older than the internet? Data scientists in this environment need more than clever algorithms to succeed, yet these additional requirements only appear when you are already in the deep end.

A data scientist must be able to think like a statistician, a scientist, a customer, and a software developer, sometimes in the same meeting! This is especially true in organisations where data science is a new function, which is most organisations.

At this event, you’ll get a glimpse at the other side of the data science “stack” - the skills and techniques that complement your technical knowledge and are at least as important to succeed.