One of the key challenges I’ve faced in my data science career is translating findings from exploratory analysis into scalable models that can power products. In the game industry, I built several predictive models for identifying player churn, but it was always a struggle to get these models put into production. I’ve written about some of the processes used to productize models at Twitch, but each product team required a unique approach and different infrastructure.
The more that a product’s features overlap with a customer’s problem space, the more utility a solution provides. Problem roadmaps help you better understand the problems and then which features to build in order to create the maximum utility.
But this didn’t feel right. Nobody becomes a data analyst so that they can tackle endless streams of reporting & data pulls. There was no ownership over the end result — the actual decisions being made. We were just API’s to providing summarized information.