Q&A with our new SVP of Science Mike Ryan
We’re excited to introduce Revionics’ new Senior Vice President of Science, Mike Ryan. We recently sat down with him to find out his views on science, pricing, diversity and what he’s currently watching on Netflix (it can’t be all serious).
Q: What are some interesting companies you’ve worked for? And cool projects you worked on?
A: ESPN is a pretty cool company that I worked for. ESPN does everything from satellite transmission to machine learning. Another cool company I worked for was Ticket Network, which I really enjoyed. While there, I worked on projects that affected the ticket brokers. It was really interesting from of a science standpoint.
Q: What lead you to data science?
A: I basically had two careers. My first career was in building systems for semiconductor design companies. That was an interesting experience. And this is going to sound weird, but I had a startup electric car company. I started to think about pivoting the company and developed a system and prototype for doing range prediction based on historical driving habits. And I was using machine learning for the first time.
Q: How do you think science is changing retail?
Promotions have always been a part of retail and now the trend is toward personalized promotions. At Revionics, we’re using science to help retailers understand the valuation and pricing dynamics related to their customer base. And we will give retailers the ability to compose a more targeted understanding of customers and marry that with the wholesale understanding of elasticity in pricing dynamics. Taking two different problems and making them fit together for a whole system is where the complexity lies.
Q: Why Revionics?
A: There were two really big reasons. One was that I wanted to make sure wherever I went next in my career, the value proposition for the company–really the center of what made the company successful—was focused around data science because that’s my superpower. And you can only do that if it’s the focal point of the product. And at Revionics, it is. The other reason had to do with the team. I was happy with, frankly, the level of motivation and intellect of the science team.
Q: Why do you think diversity is important across your team? Having men, women, and a range of ages?
A: To me, you must have diversity in a data science team, or you will certainly miss things. You will certainly not get a full point of view. And when you don’t look in a corner, that corner is likely to have something that may have a deleterious effect on your final outcome. You need people to expose all the different sides of a problem. Diversity has been shown in all kinds of fields, including data science, to be an important aspect of that.
Q: Where do you see AI in 10 years?
A: I think the robots are going to destroy the world. No – I’m joking I wouldn’t even venture a guess. I don’t think you’ll get a credible answer from a single human being
Q: Could you get the answer from a robot?
A: That may be true yes – I guess what I’m really saying is that AI is changing so fast and the computational and processing power and the ability to deal with larger and larger scale is moving right along with it. So as the techniques and methods in artificial intelligence grow and the power to deal with that complexity grows along with it, there’s no limit to where it goes.
Q: What advice would you give young professionals breaking into the industry?
A: There are a lot of tools and frameworks out there to get a jumpstart on your career. Machine learning isn’t just about going deep into mathematics anymore – it’s also about having a passion for forecasting. You also have to be good at solving problems. And then I think the thing that makes a difference between people that do data science and those that do it really well is this: primary motivation for doing your job should be intellectual stimulation. If that isn’t a thing that really makes you happy, then it’s not a good place to be.
Q: What are you currently binging on Netflix?
A: Well, that question needs to be answered in the past tense. There’s nothing left – I’ve watched pretty much all of it since we are at home. Just kidding – but I am excited because Westworld’s new season has finally come out. But they’re trickling it out to us in these weekly episodes, which is torture.