In our data-driven world, delivering for clients is no longer as simple as staffing for sales, accounts and operations. There's a new duo making the rounds: the data scientist and the sales executive.

At first glance, you might focus on the stark contrast between them. It's like the pairing of John Voight and Dustin Hoffman in "Midnight Cowboy" or Chris Tucker and Jackie Chan in "Rush Hour." Yet as the tale unfolds, they somehow gel and help each other along.

The thought of a quant-y, algorithm-y guy selling media may frighten some. Will he or she confound the CMO who is still scratching his or her head about automated audience-buying? A few years ago, an industry friend of mine asked his chief data scientist to accompany him to a pitch. The idea was for him to sit silently in the corner, and look smart, just to show off the intelligent guy who built the algorithms. But in the ad-tech world now, a land of upstart CEOs, the companies are in fact run by nerds. They've become cool. It is classic syllogism -- big data are cool, and big data are managed by quants, therefore, quants are cool.

Thanks to "Mad Men," advertising still has the reputation for slick two-hour-lunches and mohair-suit-clad sales guys. But given the increased requirements of ad-tech, and the specialties of the sale, the make-up of the team has changed. Tech leads the space. Is it so crazy that data guys could sell the product?

Marketers' questions are getting more technical during pitches. It's hard for traditional sales people to answer them when on their feet. Furthermore, the people asking questions don't always understand the answers. The call and response requires a subtle re-framing of the questions to educate and create buy-in. This is not purely relationship selling.

Unlike a technical-enterprise sales pitch, media selling hasn't historically had the need for a position like the sales engineer. Data scientists are now the media-sales equivalent of the sales engineer. Online media companies historically sold networks and sites the same way someone sells watches: silver, gold, big face or small. But now, when display advertising is becoming commoditized and algorithms are potentially the only differentiation, the tech world needs a data-versed seller who can get down in the weeds while making it all seem not so scary. The pitch is far less about inventory and audience and more about how predictive modeling works and what insights the technology can provide.

Consider the most stereotypical of sales pitches: the car. There's an engine, body and four wheels to get you from point A to point B. It's interchangeable, one company to the next, and nearly anyone can sell them. For a brand to resonate and thrive, it needs a more advanced sale. Think about Mercedes, which sells its science, in terms of engineering and manufacturing. It doesn't sell cars, but well-engineered machines and ideas.

The differences between tech companies are intangible, but they exist, in unique data sets and algorithms. What we've done historically doesn't play in this new world of data and science. Our media world is increasingly driven by programmatic strategies, the sales pitch is changing, and we need to adapt with that. We can't ignore the fact that the data scientists, nerds and quants have become the cool kids now.