Mark Kindem can thank his parents and brother for getting him started on the road to being a statistician. “My dad was a baseball card guy,” Kindem said. “I used to pore through data as a kid.”
Kindem and his brother would line up baseball or basketball cards on the living room floor, study the stats, compare the players, create a tournament bracket and predict who would win.
“I remember my mom -- when I was about 9 years old – looking at us saying, ‘You can use statistics as a career,’” Kindem said. “And I remember thinking, ‘You can actually calculate baseball cards’ statistics as a living? That sounds like the best kind of job.’”
The glamour of statistics
Although his dad encouraged him to be practical and to use his intelligence in math to become an engineer, Kindem chose biostatistics as his major at the University of North Carolina-Chapel Hill, graduating right about the time the notion of big data was becoming popular.
“Statistics was on the rise as a glamorous field to get into,” said Kindem, and the wide variety of applications drew him in. “With statistics you can learn about anything. Most business and scientific fields require data analysis, so it is a widely applicable skill.”
He spent a year after graduation at Research Triangle Institute working on survey statistics, but he realized he needed a master’s degree to do more interesting things in statistics, so he got a master’s in statistics from North Carolina State University in 2006. In his spare time during basketball season, he built statistical models to predict the NCAA Tournament winners.
Then he got to do it for a living at Bank of America, where he built models to predict which customers were most likely to respond to mail offers and sign up for new deposit accounts.
“It wasn’t ever my goal to find a career that also felt like a hobby, but I ended up in one and I feel lucky that was the case,” Kindem said.
After another stint at RTI doing public health research and drug intervention trials, Kindem was ready to combine his consulting, forecasting and predictive modeling experience at SAS. “I applied online and got a call for an interview three weeks later.”
Optimizing prices with statistics
Today at SAS, Kindem is an analytical consultant for Global Professional Services and Delivery, with a focus on SAS® Revenue Management and Price Optimization Analytics.
“This solution does pricing for cruise lines, hotels, car rental agencies -- anything that sells tickets, takes reservations and has a perishable supply,” Kindem explained. “Our solution helps them optimize their price in relation to their competitors and their customer segments.”
Take business and leisure travelers as an example. “A business traveler will tend to pay a lot more for an airline ticket or hotel room than a leisure traveler, but the business traveler may book closer to the date of use than a leisure traveler,” Kindem said. “The question then becomes how do you optimize the number of tickets you will sell to a leisure travelers versus the number you need to reserve for business travelers?”
With SAS RMPOA, customers can forecast the demand based on historical evidence and set limits accordingly.
Statisticians are "the first to know"
Kindem works on a global enablement team that helps consultants around the world implement SAS solutions. “We provide boot camps, interact with them and get feedback, conduct exit interviews from the field to get input on what’s working with the solution and what’s not so that we can take that feedback back to R&D in order to improve the product.”
“I’m more of the hands-on analyst and I specialize in forecasting,” Kindem said. “Although I’ve been programming in SAS for about 10 years, now I have to learn all the subtleties of the SAS RMPOA solution. To configure this solution, you have to know how to program in SAS really well. I have to distill it down to what’s important and what’s not so we can get someone up to speed as quickly as possible when boot camps are delivered.”
The field of statistics continues to intrigue Kindem. “All lot of key learnings in science and business are through data analysis,” he said. “As a statistician, it’s exciting to tell people the results of the analysis. You’re the first person to know.”
Learn more about Mark Kindem in this Q&A
We've been profiling many SAS statistical employees for the International year of statistics. Read more about Mark below, and then check out the SAS loves stats series to hear from other smart statisticians.
What is your advice to students?
- Take as much stats as early as you can. The earlier you can do it, the better, even if you are just fooling around in MS Excel. If you are a novice, just play around with it, but you will see that SAS can do a whole lot more.
- There will come a point when the underlying math becomes difficult, but don’t be intimidated by statistics.
What should employees know about the field of statistics?
- Results of statistical studies don’t imply certainty. Everything you learn is reported with a degree of probability (e.g., you can’t say if you smoke then you’ll get cancer … you can say that if you smoke your chances for getting cancer greatly increase).
- Statistics isn’t as intimidating as it seems. I sense people who aren’t in statistics have no confidence in citing statistics. While that is partly encouraging to me because it means people are being careful about what they say, I don’t like to see people who aren’t confident. You might know more than you think so don’t shy away from using statistics.
- You have so much free statistics education at your disposal here at SAS. Take a course. It’s a shame not to take advantage of the educational opportunities here.
Who is your favorite statistician?
Bill James, who is [at]the forefront of baseball analytics. He works for the Boston Red Sox and has invented new statistical measurements related to baseball that are completely new to the field.
What do you like to do outside of SAS?
- Collect baseball cards.
- Play tennis and badminton with my fiancée (I hold weekly tournaments in my backyard).
- Read (recently finished A Midsummer’s Night Dream, Cloud Atlas by David Mitchell, Paul McCartney’s biography and a book on baseball analytics).