As a child growing up in Nigeria, David Olaleye would follow his dad, an auto mechanic, as he drove to work every morning. So he always thought he would end up being an engineer in the automobile industry.

But when he went to college at the University of Ife (now Obafemi Awolowo University) in Nigeria, he could not secure a spot in the mechanical engineering degree program, so he studied his second choice: statistics.

“I always loved working with numbers,” said Olaleye, who was also fascinated about the notions of chance and probability, even as he played cards with friends.

In college, he began to see statistics as a way of explaining things and made the connection between what he was learning and the games he played as a child.

“These mathematical expressions explained what I knew intuitively when I tried to guess what cards my opponents had,” Olaleye said. “We make decisions every day of our lives -- tough choices. We need data and statistical analysis to make an informed choice.”

After getting his bachelor’s degree in statistics, Olaleye worked in the Office of Statistics in Nigeria for three months, then got his master’s in social statistics so he could apply the theories he learned as an undergraduate. He also taught introductory statistics to first-year college students.

He got a training scholarship to work on his PhD degree on demography and population studies at the University of Pennsylvania in Philadelphia. “Statistical study of human population encompasses three areas: birth, migration and death,” he said.

While writing his dissertation, he worked as an assistant systems manager at the University of Pennsylvania Medical Center, where he was introduced to clinical trials.

“I love the idea of working on things that actually impact human lives.” David Olaleye

“I worked with physicians who were writing protocols and looking for research support and grants to do clinical trials for new drugs,” he said. “My goal was to help them with data collection and data analyses, and do SAS programming.”

The hospital environment is where his real interest in statistics began. “I love the idea of working on things that actually impact human lives,” Olaleye said.

After graduate school, Olaleye first worked at Organon, a pharmaceutical company in New Jersey, where he wrote statistical analysis plans for Phase 2 and Phase 3 clinical trials. He joined SAS in 1999 as a biomedical engineer and still works in the same group he started in, although the department names have changed over the years.

Working in Health & Life Sciences R&D today, Olaleye develops analytical routines and statistical models for the SAS^® Health Outcomes Analysis solution. Using observational health care data, medical researchers and clinicians can use this solution to perform clinical research and comparative effectiveness analysis of new treatments. The advanced analytics embedded in the product may be used to discover which combination of treatments work better and can improve clinical outcomes in different diseased populations.

“Being able to provide researchers with clinical data in digestible format that will facilitate health decision making is very important because a physician can look at the consolidated data from the people who were treated before to garner insights on how best to provide care for his or her current patients,” Olaleye said. “I have an opportunity to work on a product that can help improve human lives, especially in the area of cancer treatment.”

This work keeps him excited about statistics and his job at SAS. “Being able to work with bright folks at SAS and knowing that we have not just the expertise, but we can also develop products that can help in addressing this problem.”

In his prior role as a systems engineer and analytical consultant, part of his job was to team up with the sales force to provide industry domain support and demonstrate SAS products. “I also gather customer requirements to help us decide new features that are needed to address problems faced in the industry,” he added.

Olaleye is excited about the December release of the SASHealth Outcomes Analysis Solution. “It provides a 360-degree view of the patient,” he explained. “Clinical profile of the patient will be at the fingertips of the clinician.”

The “beauty of the product” is that it demonstrates SAS’ strength in analyzing the massive amount of electronic health data being collected each day, Olaleye said. “With the different analytical products that SAS can boast of, we can provide useful information that the physicians need to deliver optimal medical treatment resulting in the best outcome with minimal amount of adverse effect.”

Learn more about David Olaleye in this Q&A, and read about other statisticians in the SAS loves stats series. Also, be sure to check out our International Year of Statistics page for more statistics resources.

What should readers know about the field of statistics?

• Statistics is one of the very few subjects that many disciplines rely on to make informed decisions.
• Clinical trials and post-marketing drug safety studies rely on statistics to help us determine the efficacy and safety of new drugs and for proactive monitoring of approved drugs being sold to the general population.
• “Good” data provides us with information to make informed choices on important matters. As a personal example, I now have access to my own health care records. I am able to use the data to monitor my blood pressure and cholesterol levels, and the need to modify my diet and physical exercise habits should the numbers go “out of whack.” If I don’t have good control over these conditions, it could have a negative impact on my health and longevity.

What is your advice to students?

• We live in a data-driven age, and there will always be a job. We need more statisticians to help make sense of and guide policymakers on how best to use data to inform policy decision-making.
• The volume of data will never decrease!
• Engineering, medicine, social work and most job disciplines need people with knowledge of statistics to help make sense of massive amounts of data we collect daily.

What is your favorite statistics blog/journal?

• Journal of Pharmacoepidemiology & Drug Safety
• New England Journal of Medicine
• American Statistician
• Rick Wicklin’s blog
• KDD (Knowledge, Data Discovery) data mining blog

Who is your favorite statistician?

• R. A. Fisher
• Jim Goin (recently deceased). Jim took me under his wings and taught me all I needed to know about clinical trials and helped develop my clinical and SAS programming skills.

What do you like to do outside of work?

• I love reading, especially the Bible and other inspirational books, scientific articles and also James Hadley Chase novels.
• I do enjoy spending quality time with my wife and three daughters. I also enjoy traveling and have taken mission-related trips to Romania and Mexico.
• I mentor youths in our church about life-decision choices. I tell them each decision they make is a data point -- they collect information along the way that guides them and helps them predict what lies ahead based on their current choices.