At Northwestern University Feinberg School of Medicine, Mary Kwasny is conducting research designed to help pregnant women reduce unhealthy weight gain.
At Groupon, Zahra Ferdowsi’s research is helping the Chicago e-commerce marketplace company better target merchants most in demand from deal-seeking consumers.
Both work in data science, a STEM field that mines through mountains of big data to find patterns and solutions that help in business, medicine, government and other sectors.
Data scientists are among Glassdoor’s 2015 top 10 hottest professions. The career requires a love of statistics, which women have found attractive. More than 40 percent of degrees in statistics go to women, notes David Morganstein, president of the American Statistical Association.
The data science career also requires analytical, math and computer programming skills, along with communication skills necessary to translate one’s findings to decision makers.
And it pays. The average annual salary exceeds $100,000, according to Glassdoor, an online job review site.
Data scientists are employed in a wide range of fields. They’re helping candidates get elected, the Federal Reserve Board decide monetary policy, and physicians make better treatment decisions based on personalized medicine, said Michael Walker, president of the Data Science Association.
At Groupon, Ferdowsi developed algorithms to help the company determine “what our customers are going to truly love to keep them coming back, but also which local merchants are likely to best fulfill that demand,” said Angela Han, the company’s data science manager.
Before joining Groupon, Ferdowsi, 36, said she was part of a research project at DePaul University evaluating and modeling changes in Chicago neighborhoods “that may lead to gentrification or abandonment and ultimately to the loss of affordable housing.
“I used demographic and soci-economic data . . . neighborhood data and housing characteristics to make a typology of the city of Chicago. This map of the city helped to understand the characteristics of Chicago neighborhoods. Also, using the past 30 years of census data helped to understand the changing patterns across similar communities.”
The Lincoln Park resident is working on her Ph.D in computer science and has a bachelor’s in computer engineering and a master’s in IT systems.
Laurie Skelly was pursuing a career in neuroscience, when she changed course and decided to become a data scientist. The 32-year-old Roscoe Village resident said it’s perfect for a “nerdy and creative young woman like myself.”
She works for Datascope Analytics, a Chicago data science and design company. Among projects she has worked on is software that tracks what’s being said about a company’s products in online forums, reviews and comments; and an analysis of whether the opening season point streak of the 2012-2013 hockey season meant Stanley Cup victory for the Chicago Blackhawks. She also has built data tools for a local nonprofit to help its clients access and work with its library of research and reports as they do research.
Kwasny, who holds a doctorate in biostatistics, loves the profession.
“I like that it can be different every day, depending on the projects and where I am in those projects,” she said, noting she has been involved in studies assessing how dietary patterns affect cognitive function in aging populations and analyzing data to determine whether diabetes or smoking affects recovery after orthopedic surgery.
“It’s collaborative, and I can learn about many different fields of medicine,” Kwasny said. “I’m always learning, and I’m always helping other people learn.”
Ferdowsi finds most rewarding “the actual impact that your findings can have in an organization. You build something. You find something, and the company uses your model and findings, and you can see how much benefit everybody can have from your findings. You might find something that no one can think of, and that’s very, very exciting.”
Skelly enjoys “the freedom we have right now. It’s a new and a broad field to invent new things. You feel kind of like a trailblazer.”
And that also brings challenges.
“You are never done with your training,” Skelly said. “There are just so many programming languages and tools and algorithms, statistical techniques that you need, and you can only ever learn the next few that you need for this project. And also the shelf life of the technical tools is not that long. So our entire career will be constantly training, which is fun a lot of the times, but it can be daunting. You never get that satisfaction of here’s my toolkit. I’m an expert. I can rest. The skill acquisition will be forever.”
The data itself is a big challenge, according to Ferdowsi.
“All the companies have been saving and tracking all this data, but the thing is that data is not always high-quality,” Ferdowsi said. “It’s not perfect, so you need to work on data to find inconsistencies or results before you can go forward and do any kind of analysis.”
The field holds opportunity for women.
“We could face a shortage of up to 200,000 people with the skill set necessary to do this type of big data analysis,” Morganstein said.
“This is going to continue to be a hot area because we’re going to need people to interpret meaning from the data using scientific methods,” Walker said. “We’re coming out with new technology that’s becoming cheaper. There’s more abundant data that’s allowing organizations, both public and private to be able to use this data to get a competitive advantage or create some sort of value. It’s difficult to do, as some organizations are finding out.”