As the complexity and size of data samples increase, once lightly regarded position now key for programmers

New York — “It’s kind of a BS term,” said Haile Owusu, discussing his “data scientist” title at Turner Networks at a morning TV Data Summit panel Wednesday.

Owusu largely had his tongue in cheek.

“There’s a challenge in combining these data sets to tell a coherent picture of a [viewer],” said Owusu, who noted a Turner colleague whose daughters and wife all share his Spotify account, and contribute to his user profile. “That data,” Owusu noted, “serves no one,” at least without someone around to interpret its complexity.

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Putting his initial self deprecation in context, Owusu said that the importance of data science for programming network and platform operators has increased quite a bit from when data sets were mere samples of a few hundred or few thousand viewers, and into an age which factors in machine learning and artificial intelligence.

The panel, part of Future’s NYC Television Week event, included representatives from multiple Automatic Content Recognition (ACR) technology vendors. They weren’t buying Owusu’s assertion, either.

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Noting the complexity of blending myriad water marking techniques, and data sets of millions coming from multiple devices, Jason Bolles, senior VP and managing director for Gracenote Video Personalization, said, “Data science is really the key to all of this stuff.”

Responded Owusu: “That is correct.”