Data scientist? AI prompt engineer? Or both?

Data scientist? AI prompt engineer? Or both?

Data scientist? AI prompt engineer? Or both?

As AI transforms medical marketing, data and analytics roles have both evolved and expanded.

As recently as five years ago, many health marketing firms lacked an in-house data operation. Now nearly every organization has multiple data scientists on call — and, with the arrival of generative artificial intelligence models such as ChatGPT, these operations have become more sophisticated.

But with this increase in sophistication has come yet another shift in traditional data- and analytics-oriented roles. It’s as likely as not that an organization’s top data person has already been tasked with a range of AI-related responsibilities, most notably as prompt engineer.

We asked four data/analytics pros to tell us how the traditional data scientist role is evolving to accommodate these new types of assignments.

Sayee Natarajan, president and CEO of RxDataScience, which Syneos Health acquired in 2021, acknowledges the obvious right up front: that, since the debut of ChatGPT and large language models in general, most companies’ approach to AI has changed. “Everyone is surprised at how well the models work and how fast they’re maturing. We’re just beginning to grasp how this will change every single person’s job,” he says.

Until now, Natarajan notes, people working in data needed to understand some technology, the domain and the data. But today, those same people need to be able to write a well-constructed AI prompt.

“AI is very sensitive, and if you use the wrong language, it doesn’t answer the question properly,” he explains. “The ability to rephrase a sentence repeatedly is a very useful skill. You cannot succeed if no one on your team can write well.”

That’s why Natarajan has expanded his team to include data aces and technologists who understand processes and workflows. “AI is becoming easier to program. So now the limit is not so much how well you can write code, but more how well you understand the problem and can communicate it — not only to the LLM, but to the stakeholders as well.” (“Large language model”  is a general term for AI technologies such as ChatGPT.)