Agile development is a well-established practice for modern software development that gained broad adoption as software became ubiquitous in the business world. As data science matures in the organization, perhaps we are at a similar crossroads. What can data science learn from the agile approach? I’ll share my experience as a data scientist in an agile product development group – what agile practices have proven most valuable, how R has enabled an agile approach, and where data science may need its own set of agile principles.
Elaine McVey
VP of Data Science at the Looma Project
She specializes in building the strategic plan, initial team, and key infrastructure needed to establish the data function at startups.
