From studying engineering to consulting with Fortune 500 companies, Eric Perz revealed some interesting things about his career path and his personal life, as Brunner recently promoted him to VP, Data Science.
Q: How did you enter the ‘data science world’?
A: After completing a master’s in engineering, I was drawn to the world of consulting rather than a typical engineering job because I’d be able to work on a big variety of projects and industries. Ironically, the parts of the projects I was most passionate about were when I was interacting with the support staff of statisticians. They were coding and working directly with the data, and I decided that’s how I wanted to steer my career.
Q: What will be your role as VP, Data Science?
A: I always say I have to continue to do the work because if I don’t deeply understand it, then I can’t effectively do the things more associated with a group leader such as writing proposals, engaging with clients and prospects, and supporting innovation. I think a Data Science VP role is roughly 50% paid project work, 25% administration and strategy, and 25% innovation and process improvement.
Q: How does this promotion work toward your professional goals?
I’ve had some success in the past with integrating data science practices deeper into day-to-day agency processes. This is an opportunity to raise the bar for exactly that. Mostly due to momentum and market demand, full-service agencies have tended to constrain data science to media performance measurement. But, the function can contribute much to creative, UX, and other groups. You can find a lot of chatter about this concept but few concrete examples yet. Brunner embraces the idea too and it’s on my team to find exciting ways to do that and stay ahead of the curve.
Q: What is Data Science to you?
The term emerged when CMOs were tasked with answering hard questions about marketing ROI. Data engineers and business intelligence analysts, who in their own rights have vast technical knowledge and solve important problems, tended to not have the necessary statistical knowledge to address those tricky questions about cause-and-effect. Now, the expectations are growing for data scientists to have working knowledge about the “full stack” and not just stick to stats (e.g., app development, database administration, automation). Add to that increased focus on business acumen and soft skills. You could call data science the practice of using data to solve problems. And practitioners can fall on a very wide range of experience and skill.
Q: How will this promotion help you achieve your goals with Brunner?
A: Everyone talks about “AI” but what they don’t say is that AI in most of its forms today is not that useful to a CMO who asks about ROI. I feel I’m in a spot now where I really direct a lot of energy toward this challenge, which is how can we use the advantages of AI algorithms in a manner that also satisfies our stakeholders? I’m already excited by the promise I’ve seen in it.
Q: Lastly, What is ‘the dream’ to you professionally or otherwise?
A: From a professional standpoint, I think that’s pretty-well covered. Personally, I have two young sons so “the dream” to me is simply being a positive part of their lives as they grow and develop into unique grown-ups! It’s why work-life balance is so valuable to me. I would also very much like to restore a 70’s era Porsche.