to us asking for a model. We built a proof of concept. Got the green light. Delivered the model. Weeks of work…all to hear nothing. It’s a tale as old as time, and one that plagues data professionals everywhere, from analysts to ML engineers. So, what happened? Your Model is a Mystery Our profession is one rooted in modern computer science and technological advancements. Many of the most powerful solutions at our fingertips are ones that would have been too computationally expensive decades ago. With the reliance on the newest, most capable technical breakthroughs, comes skepticism. In data science, we have the ability to create incredibly complex models. My team alone has hundreds of standard features in our feature library that we provide to each new model build. We tune dozens of hyperparameters and use powerful algorithms that iterate over hundreds of runs to maximize predictive performance. This process can create models with incredible accuracy, but it comes at a cost: explainability.…