Great Applied (Data) Science Work

Advanced data science work in industry is sometimes also known as “applied science,” reflecting the reality that it’s about more than just data and that many former academics work in the field. I find that “applied science” has different expectations than research science. So I wrote up what, in my experience, helps produce great applied science work. I use this as a “definition of done” for data science work, but many points will also benefit analysts, engineers, and other technical roles. <h1>The Goal: What is successful applied science work?</h1> Great applied scientists solve valuable real-world problems end-to-end, by finding clever uses of data and models. Sometimes, the first step to this is discovering the most impactful business problem which is likely to afford feasible scientific solutions; sometimes, the business problem is well-understood, and scientific work begins at the formulation of a well-defined technical problem statement. In either case, successful scientific work begins with understanding a real-world problem. Scientists need to understand complex business challenges well enough to translate them into technical formulations that can be solved in finite time. They cut through ambiguity and create appropriate structural assumptions to enable solutions. <a href="https://towardsdatascience.com/great-applied-data-science-work-5739daf13dd3">Website</a>