Transitioning careers from finance and accounting background, Josephine Tom quickly learned that without the long storied track record that many employers seem to demand of even entry-level positions, she had to find every way to distinguish herself. “I realized that I needed to stay abreast of all the new tools and trends out there,” she recalls. “There’s lots of competition in the job market, and you need to find a way to stand out.” Many established professionals are looking for ways to stay relevant in the brave new business world, and they face stiff competition from surprising corners. Technical experts, like Emily Gan, are making their mark on the scene with specialized domain knowledge in science, technology, engineering, or, as in Emily’s case, medicine. Even those trained in solving complex technical challenges risk being eclipsed by younger minds like Ben Arar, geniuses who have recently finished the most rigorous mathematical programs, such as Princeton University’s undergraduate physics curriculum. As businesses scramble to maintain the slightest competitive edge using tools traditionally used only by astrophysicists and computer scientists, the world’s brightest MBAs find themselves competing with doctors, engineers, mathematicians, and scientists for positions in marketing, supply chain, retail, and even the non-profit sector.
Despite a more mathematically savvy workforce, employers are still finding trouble filling positions. Many hiring managers find that job candidates often need at least a year of learning on the job. To employers like Kaiser Fung, simply knowing how to run regression models or perform a principal components analysis is not enough. If you’re going to work at a web analytics company, employers expect you to understand how the web is structured, what kind of metrics can be recorded, and justify your use of a fancy algorithm to drive concrete business insights. Dissatisfied with the dearth of qualified applicants for his data team at Vimeo, Fung realized that he needed to build a much more comprehensive training pipeline that would produce the type of people he needs.
Hearing similar concerns from other employers at top-line consulting firms and Fortune 500 companies, Fung teamed up with Nishant Srivastava, an Executive in Risk and Capital Management at GE Capital, to establish rSQUAREedge, an intensive full-time program dedicated to training a fundamentally different type of data scientist—one that is prepared to be an expert on the first day of the job. “Investors always say that they’re looking for ‘unicorns,'” says Fung. “Employers are the same. They want unicorns who are fluent in statistics and can translate findings into actionable business insights. The people we train cover all of these areas.”
rSQUAREedge trains unicorns by immersing them in real world data problems, hiring faculty members who are the very employers looking for the students they are training. That means students like Josephine, Emily, and Ben are taught by the type of people they would be supervised by on their first job. “With rSQUAREedge,” says Ben, “I was able to connect with the instructor for my optimization class, and now I’m working with him on web analytics. I’m really happy about how it turned out.” Emily also has nothing but praise for her instructors. “Being a medical student, I didn’t come from a strong mathematical background. But the instructors were very responsive and helped build me over the learning curve.” The core of rSQUAREedge’s success in training and job placement is its faculty, who, as established data experts looking to recruit prospective team members in their respective companies, are key stakeholders in their students’ success.
The industry backgrounds of the faculty ensure that the curriculum covers exactly the skills employers seek in hires. Ben explains, “Kaiser’s class forced me to think not only about data quality, where data are coming from, or how to clean them up, but what kind of data I would need in the first place to answer the question at hand.” Josephine recalls how her data visualization class required her to find, clean, and analyze datasets. “I worked with data in previous jobs,” she remarks. “But I learned that working with data means so many different things depending on the business and what your specific role is. At rSQUAREedge, I saw a much bigger picture of what it means to work with data.”
In a market in which banks are putting people out in the streets and academic institutions are churning out far more PhDs than they can hire, job candidates need much more than Ivy League degrees and investment banking bona fides to compete amongst the best and brightest. Kaiser Fung designed rSQUAREedge to meet exactly those needs, to fill the missing pieces, whether the candidate is a seasoned financier or a world-class engineer. Employers are looking for unicorns who are able to derive business insights from complex data. rSQUAREedge is there to make sure these unicorns are found.
Company: rSQUAREedge
Address: 33 Irving Pl
City: New York
State: NY
Zip code: 10003
Telephone number 1-917-699-3463
Email address: info@rsquareedge.com