Wall Street and Silicon Valley may be 2,562 miles apart, but at Penn, finance and tech are becoming increasingly intertwined.
Eric Bradlow, a professor in the Marketing Department at the Wharton School, sees business strategy and technological competency, particularly in the way of data science, as inextricably linked skills for jobs in the modern economy. “People that can take statistical modeling and big data and turn it into corporate strategy — that’s what firms are looking for today,” he said.
Bradlow cited recent changes that Wharton has made in its curriculum to keep up with the needs of the changing job market. Wharton re-named its Operations and Information Management Department (OPIM), the Operations, Information and Decision Department (OID).
This department offers more than just a new acronym. It seeks to rigorously blend computer-based data analytics and business management decision making, the latter which has become increasingly dependent on the former.
For students not concentrating in OID, Wharton’s core curriculum ensures that all students will be familiar with basic data science techniques. Programming languages R and SQL, which are designed to statistically analyze big data, are taught in varying capacities in upper level statistics courses and in Wharton’s core curriculum.
According to Bradlow, the skills imparted in the curriculum fall into four categories: managing and handling of data, which essentially translates to setting up databases, cleaning data and querying/extracting data; predictive modeling, which involves statistics and data mining; optimization, which enables companies to decide how and when to issue coupons and set prices; and the ability to use the given data to make good business decisions.
Wharton has also done much in the way of educating its students about how technology companies have become successful using data science technology and other means. “There’s a lot of emphasis [in various Wharton classes] on management within the technology field ... in a lot of management courses there are cases of technology companies” that attribute a lot of their successes to good management,” said Eliana Mason, a senior in the Jerome Fisher Program in Management and Technology program.
Mason has been to able to reinforce both skill sets in her summer internships, which have involved working in the technology departments of banking or financial companies.
Mason has cited “being able to understand people with both of them [tech and management skills]” as key to being successful in her internships.
Wharton is still in the process of refining its curriculum to better pair the skill sets of both domains. Sarah Beckoff, a Wharton senior, has noticed a rise in the demand for courses that incorporate more programming languages and data analytic methods. She also anticipates a re-thinking of Wharton concentrations in the future, to meet both student and job market demand. Start-ups, she noted, have a growing appeal among students, and it “definitely helps if you speak a similar language [coding].”
Consulting and investment banking firms are not the only professions that rely on data science. Those interested in “data science-immune” fields can no longer perform relevantly and effectively without data science techniques.
“The days in which people are pigeonholed down a certain track should come to an end,” Bradlow said.