Is Agile Data Science a thing now?
YOW! Data 2019
How come there’s no standard text on how to operate a Data Science team? At its current scale this is a young practice without a widely accepted mode of operation. Because so many practitioners are housed in technology shops, we tend to align our delivery cycles with developers… and hence with the Agile framework.
I will argue that if a data team fits within Agile it is probably not performing data science but operational analytics—a separate and venerable practice, and a requisite for data science. To ‘do’ science we need a fair bit of leeway, although not a complete lack of boundaries. It’s a tricky balance.
In this talk I will share my experience as a data scientist in a variety of circumstances: in foundational, service, and advisory roles. I will also bring some parallels from my past life in scientific research to discuss how I think data science should be performed at scale. And I will share my current Agile-ish process at Atlassian.
Sr. Data Scientist
Growing up by the mountains of Northern Greece, Hercules Konstantopoulos developed a fascination with the night sky and all its intrigue. After a career as a researcher in astrophysics that spanned ten years and four continents, he became drawn to addressing a greater variety of data-related problems. Data science ensued with work on sustainability and energy management, and now a spot as Sr Data Scientist at Atlassian, Sydney’s most acclaimed home-grown tech shop. There he focusses on converting support tickets and behavioural data into product strategy and business direction, and on creating informative and accessible data visualisation.