If you’re a marketer, sales professional, or even an executive, working in tandem with a data science team comes with a steep learning curve. Beyond technical challenges, lack of buy-in from decision makers and misalignment between data science and business teams are two of the most common reasons data projects fail. How can data scientists and professionals in non-technical roles work better together when they sometimes don’t even seem to speak the same language?

The typical data scientist might have a graduate degree in computer science or mathematics, but that doesn’t mean he or she can’t get on the same page with someone who is focused on improving customer engagement or boosting quarterly financial results. As a non-technical professional, your first step should be cultivating a better understanding of how data science can make predictions about future business outcomes with the data you’re collecting today.

Learn the Lingo

To help you get a leg up on learning what data science is all about, we’ve compiled dozens of technical approaches, popular tools, and, yes, industry buzzwords into an interactive eBook called The Data Science ABCs. Demystify deep learning, GPUs, testing and training datasets, and more with easy-to-understand definitions and further reading from our expert contributors. You can read it here.


Meet and Greet

Step two to improving your collaboration with data scientists is easy: Schedule a meeting to talk about the goals of your project.

“It is critical that communication with upper-level management begins from the very first interaction, rather than the final output,” says Scott Murdoch, director of data science at HealthJoy.com. In Scott’s experience, detailed in his blog post “Bridging the Gap Between the Data Scientist and the Executive,” data scientists are rarely handed a neat, well-defined business problem from the outset. But that's not an issue if lines of communication are open and both data scientist and non-technical stakeholder understand the purpose of the project.

Know the Value

Half of executives have dismissed the results of an analysis because they didn’t understand them. Outcomes like this can be costly and detrimental to the future of your business; the majority of analyst firms report that missing the train when it comes to data science will result in a dulled competitive edge and eventual decreases in cash flow

Even if you’re not planning to lead a data science project anytime soon, gaining an introductory understanding of one of the most in-demand jobs today can only benefit you in the long run. Get started with our interactive eBook, The Data Science ABCs and don't forget to share!

DataScience Staff
DataScience Staff