Rethinking Fast and Slow in Data Science – Hacker Noon

The tension between long-term planning and short-term flexibility is everywhere, including data science methodology. Is it possible for product development teams to reconcile rapid iteration with the slow-moving behemoth of the deep research process, or must they pick one? Spoiler alert: not only is it possible to reconcile fast and slow approaches to data science experiments, but the lessons BrainQ has learned along the way offer a roadmap your team can follow. BrainQ's mission is to treat neuro-disorders with AI-powered technologies. If you were about to humor our discussion of agility, that probably stopped you in your tracks -- we're dealing with a behemoth's behemoth: medical research data science.