Making Data Science work relevant to your business is just a crucial as creating the work itself. This step often gets forgotten and left behind by us more technical folks. While teams build some amazing, and extremely useful tools, no one will ever use them if they don’t understand them. Technical teams, especially those in data science, need to educate and engage others in their products.

It’s also one thing to excite people about a shiny new feature but weeks, or months later, they may have found other priorities. How do we as data scientists make sure the projects we develop are useful to the business and the business knows their use? In other words how do we make sure all of our projects can, and do, add business value? In this talk I’ll focus on keeping engagement throughout the development process. Throughout my career I’ve worked with data as a software engineer, a researcher, and a biologist. I’ve seen a lot of ways good projects succeed but even more how good projects fail and have some ideas about why.

We’ll go through the technical development of a specific computer vision project on extracting color from product images. While we’ll talk about each step along the way we’ll focus on the soft skills and how to keep engagement throughout.

This talk is for all skill levels especially Data Scientists, Engineers or Data Science PMs looking to demonstrate the business value of their products. It will likely be most helpful for early to mid-career individuals.