Although the term “data scientist” has a nebulous definition at best, there are a few characteristics that seem to unite us: we are curious, we like finding nuggets of information buried within a mass of data, we like solving hard problems, we are technically inclined. There are tons of fantastic programs offering master’s degrees in data science and analytics, and these programs teach statistics, data mining, machine learning. But what if you need to build an actual product that is used by people? Does knowing the mathematics of back propagation help you? To our knowledge, most data scientists are not trained in product development. Yet, products that are underpinned by machine learning are becoming essential tools for many businesses, particularly in the retail and eCommerce space. Building data products require data scientists, but as a whole, we are…not really great at building them. How can we contribute our talents to this process without derailing it and making our product development leadership roll their eyes and cringe?