When the winner of TDA@OhioState’s challenge at the OHI/O hackathon was announced, the team’s name had a familiar ring it to: Joan Cena.
The takeoff on the “JOHN CENA” Internet meme, in which the muscle-bound wrestling star’s theme song and likeness pops up unexpectedly, was intentional. “We wanted to celebrate that we were a team of four girls, which is rare at hackathons,” says team member Claudia Hinkle. Of the group (pictured above), Hinkle is the lone Computer and Information Science major; the rest of the team—Edrienne Co, Sophia M. DeRosa, and Ariane Krumel—are majoring in Computer Science and Engineering.
With data science among the fastest-growing and most specialized job markets in the country, workforce development is one of TDA@OhioState’s top objectives. For OHI/O, TDA and the College of Arts and Sciences partnered to create a challenge to shed light on possible disconnects between data analytics employers and job-seekers.
Held Nov. 14-15 in the Ohio Union and organized by several student groups advised by Asst. Professor Arnab Nandi (Computer Science and Engineering) and Assoc. Professor Meris Mandernach (University Libraries), OHI/O had more than 500 participants, 107 teams, 60 judges, and 70 mentors. The 10 teams that chose TDA’s challenge were charged with developing algorithms to study two datasets from Arts and Sciences that consisted of 91 anonymized student resumes and 262 employer descriptions for full-time jobs and internships. They were to identify similarities and differences between the two, visualize the results, and make recommendations to address issues they discovered. TDA and the college judged the results on creativity, depth and value of findings, effectiveness of visualization, and quality of recommendations.
To win the challenge, Joan Cena wrote several tools to compare majors and minors, common skills, and job types, including lexical analyzers; a keyword extractor with stop words to weed out meaningless content; and Tokenizer, which they based on a previous project they’d done in a software design class. According to Hinkle, they used an external library, Apache POI, to parse the data from the Excel spreadsheets.
“Our biggest challenge was how to connect ideas that are conceptually related that don’t have words in common, so we focused on the portions of data with less ambiguity first,” she says. “To analyze the data more thoroughly, we would probably take advantage of more existing language analysis tools. For the hackathon, though, we really wanted to challenge ourselves to create as much original work as possible.”
Among Joan Cena’s discoveries was a difference in terminology used by employers and job-seekers. “Many employers use more general descriptors, such as ‘quantitative and analytical ability,’ while students commonly put more specific examples of their skills, such as their experience with a particular data analysis software,” says Hinkle. While these ideas are conceptually related, “it’s hard for a program to understand these connections, which could cause issues when searching for jobs or employees using an automated service.”
In addition to thinking about their skills conceptually, Joan Cena concluded that job-seekers would also be well-served to emphasize their distinguishing skills and experience. “One of the most important things for students was to carefully curate what they were putting on their resumes,” Hinkle says. “Just because they have a skill like Microsoft PowerPoint, which was one of the top skills listed on student resumes, including that is most likely not the best use of space since employers are looking for skills that not everyone has.”
Joan Cena’s final recommendations: Employers should seek out a specialized candidate pool to increase the likelihood of finding the skill sets they’re after, and students should develop more technical skills.
Based on the team’s findings, TDA is creating a data analytics resume template and tip sheet for students with advice on wording resumes, searching for data analytics jobs, and prepping for interviews, as well as a tip sheet for hiring managers that covers job description wording and locating students with data analytics skill sets.
“The Joan Cena team gave us some high-quality ideas for connecting students with data analytics internships and jobs, and employers with the skilled data analytics workforce they need,” says TDA Program Manager David Mongeau, MS, MBA, who served as an OHI/O judge. “We’re putting their great hacking to good use.”
In addition to the content of their work, Joan Cena stood out for their presentation skills. “The skilled workforce that employers talk about needing includes those who are capable of engaging an audience and really communicating the relevance of their data and analysis,” Mongeau says. “Joan Cerna did just that. They were able to articulate not just what they did but also why their work mattered.”
For their prize, each Joan Cena member received a $250 Apple gift card and a TDA notebook and business card holder—plus an added bonus: insights for future job searches and an appreciation for what is possible, even on a tight deadline.
“The most surprising thing I learned is how much you can get done in a day,” Hinkle says. “I’d never done a hackathon before, but I was really impressed with what we were able to achieve in just 24 hours.”