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Cornell Tech-funded startup launching bootcamp for data scientists

Jaikumar Vijayan | May 2, 2014
Advanced academic backgrounds in statistics, mathematics, and other science and technology fields usually provide the raw analytical skills required for a data scientist's job. But even with such skills, some additional prep work is generally needed to handle such a job in private industry.

Advanced academic backgrounds in statistics, mathematics, and other science and technology fields usually provide the raw analytical skills required for a data scientist's job.

But even with such skills, some additional prep work is generally needed to handle such a job in private industry. The Data Incubator, a New York-based startup with funding from Cornell Tech, aims to do just that by offering a six-week bootcamp with programs designed to prepare science and engineering PhDs for careers as data scientists and quants.

The program is the brainchild of Michael Li, a former data scientist at Foursquare and a PhD in computational and applied mathematics from Princeton University, who used his experience transitioning from academia to private industry to design the program. The bootcamp will focus on helping academics sharpen their programming, communications and business skills.

Many large companies are literally awash in data and are desperately seeking people with the skills to help them extract business value from it. Therefore, solid academic backgrounds in computational and applied mathematics, statistics and other STEM areas are a hot commodity these days.

Li says job applicants with the unique combination of analytical, programming and communication skills needed to extract business value from massive, often chaotic data sets are hard to come by. People with deep programming skills often lack the analytic acumen for the job, while those with the analytical chops generally don't have the coding skills or industry knowledge, he added.

The six-week Data Incubator program will mentor academics in both the technical and non-technical skills needed to become top data scientists.

On the technical side, the program offers mentoring in areas like natural language processing, hypothesis testing, predictive modeling and data visualization, as well as classes on using programming tools like Python and NumPy, and on database and parallelization technologies like Hadoop and MapRed.

Program fellows will be guided through a portfolio project to demonstrate their skills and techniques as data scientists.

The bootcamp is free for those selected to attend. Companies that hire graduates of the program will be required to pay the candidate's training costs, Li said.

There is a huge burden in terms of time and resources that companies have to put into finding data scientists job, Li said. "You have to spend a lot of resources to figure out if someone who is good on paper in really good."

The Data Incubator program can identify how much difficult-to-learn math and statistical skills the students already have, and thus knows exactly what's needed to meet the criteria for a data scientist.

Getting into the program will be harder than getting admitted to Harvard University, promises Li. Fewer than 5% of the 1,000 individuals have already applied to participate in the inaugural bootcamp have been accepted. Li plans to conduct a minimum of four bootcamps annually.

 

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