Looking for interesting data science problems? Mike Rimer has found new challenges at Adobe every day for seven years—no end in sight.
Seven years ago, Mike Rimer was working as a data scientist at Omniture. He remembers the day he heard the news: Adobe had acquired Omniture, and things were about to change—in some very good ways.
“I was working with a lot of talented people on some really interesting problems, and Adobe brought even more interesting problems for us to solve,” Mike says. “Today, with complex, large-scale systems crunching approximately 51 trillion customer data transactions in the past twelve months, we have new problems to solve every single day.”
Academically, Mike came from a computer science background. But digging deeper into his past reveals that his first love was the creative arts.
“From a very young age, I saw the computer as a uniquely powerful and special tool for creation,” Mike says. “I loved drawing and art, and it’s gratifying to work at a creative company that lets me leverage those skills too. I feel my work is a creative endeavor as much as a technical one.”
Today, Mike’s work involves solving an increasingly common problem: As data science technology proliferates, more and more people are trying to use data to solve all kinds of problems. That means non-technical people—marketers, executives, nonprofit organizers, small business owners—need to understand the data they’re collecting and find the needle-in-a-haystack insights that will help them optimize their businesses.
“You can use data to find main trends and key drivers of what’s going on with your customer base,” Mike says. “You can discover how customers want to interact and how to facilitate a relationship with them.”
Mike and his team are also working on putting that data and insight into the right hands, because not everybody approaches the data from the same angle.
“As that info moves from one group to another, some of it might be lost—like playing a game of telephone,” Mike says. “There are many ways of looking at any given set of data, so we have to put it in a different context for different people depending on their roles.”
Mike’s most recent work is around automated feature extraction and contributing factors discovery, but he says he sees his job as more than data crunching and algorithms. Above all, his work is about connecting people.
“Being able to provide companies with a clear understanding of how to work with people is important and exciting,” Mike says. “Up until now, it wasn’t clear how companies should interact with all of their different types of customers. I like facilitating those lines of thinking and helping make connections between people.”
Interested in joining the Adobe team? Check out available career opportunities for data scientists at Adobe or read more stories about Adobe data scientists.
Photo credit: Alex Vaughn
