Is This Candidate Real? Hiring Data Talent When AI Can Fake It, with Jeff Pierantozzi, Ep #44

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Is this person real, and did they actually do what’s on their resume? Hiring managers have always asked those two questions. AI has made both harder to answer, with polished resumes, AI-written work samples, and even deepfake interviews. Gartner predicts that by 2028, one in four candidates worldwide will be fake.

Jeff Pierantozzi has built and hired data teams over a 30-year career and has taught software engineering at Rowan University for nine years. He joins Jodi to talk about how the interview is changing, why the human part of the work matters more now, and what he looks for when two candidates look the same on paper.

“Anybody can put that technology on their resume.” – Jeff Pierantozzi

3 Things to Try in Your Next Interview

  1. Ask how it got to production. Anyone can list a tool. Ask who they worked with, what got in the way, and how the idea turned into something people used. As Jeff puts it, if they didn’t actually do it, they won’t be able to talk about the people they had to work with.
  2. Watch them think. Live sessions and case study walkthroughs show you how someone reasons, not just how polished the final product looks.
  3. Ask what they taught themselves recently. Jeff’s go-to question for spotting a lifelong learner. Any subject counts, even fixing the porch steps.

What Jodi Is Hearing From Clients

“One client had two finalists turn in work samples. One was very polished, and she felt AI had written it. The other had some mistakes, but she could see how the person thought. She hired the one whose thinking showed.

The other message I’m hearing loud and clear: companies want data people who are interested in learning the business. You can’t stay siloed in your technology anymore.

If you’re working through this on your team, I’m always happy to compare notes.”

In This Episode

0:02:01 Did You Actually Do This? Why employers now want to hear how your work got into production, not just what tools you know.

0:07:34 The AI Arms Race in Hiring: Tools that feed candidates answers, tools that detect deepfakes, and what the rise in fake candidates means for hiring teams.

0:11:38 Polish vs. Potential: What Jeff looks for when he hires, and why he weighs potential over experience when two candidates look alike.

0:16:48 Help or Shortcut? How to tell whether someone uses AI to add to their work or to do the whole job.

0:22:32 AI Exposes Bad Data: Why bad data used to stay hidden, and why a person still has to define what the numbers mean.

0:24:08 Data People Have to Learn the Business: Talking revenue with finance and leads with marketing, and why communication is part of the job.

0:26:40 The Question to Add to Your Interviews: Jeff’s question for spotting a lifelong learner.

About Jeff Pierantozzi

Jeff Pierantozzi is a data leader who has built and hired data teams over a 30-year career. Most recently he owned the analytics platform at a transportation SaaS company, running three revenue-generating analytics products. He has built data products that brought in more than $5 million in regulated industries like transportation and legal. He has taught software engineering at Rowan University for nine years.

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