BOSTON, Mass. – Feb. 11, 2016 – Machine learning automation pioneer DataRobot, Inc. announced that it has closed $33 million in Series B financing, bringing the total investment in the company to more than $57 million. New Enterprise Associates (NEA) led the round, which also included Accomplice, Intel Capital, IA Ventures, Recruit Strategic Partners, and New York Life.
With customers and offices already established in Europe, the Asia-Pacific region, and the United States, DataRobot is funded for aggressive expansion in global sales, marketing, business development, engineering, R&D, and strategic initiatives at all locations.
“We applied our first investment towards building a solid platform rather than marketing and publicity,” said Jeremy Achin, the Company’s CEO and Co-Founder. “We hired the world’s top data scientists and software engineers to create the industry’s most usable machine learning platform. Then, we focused on ensuring our early customers’ success. This additional investment will allow us to bring our solution to many more customers around the world, and to further democratize data science across all industries.”
DataRobot shrinks the data science project backlog that is growing in many companies due to the serious shortage of machine learning skills. The company captures the knowledge, experience, and best practices of the world’s top data scientists and transfers them through practical education and software automation to users of all skills levels. DataRobot enables data scientists, statisticians, business analysts, and software developers to build and implement predictive applications using open source and custom machine learning algorithms, in industries including financial services, healthcare, life science, marketing services, and others.
“We’ve seen the evolution of transformative advanced analytics technology within our portfolio, from Tableau turning data analysts into business analysts, to DataRobot turning business analysts into data scientists,” said Harry Weller, General Partner at NEA. “The DataRobot platform empowers users to easily build fast and accurate predictive models, something that previously required time-intensive labor by expert data scientists.”
“Unlike most startups in this industry, DataRobot was founded by – and is run by – applied data scientists, not serial entrepreneurs looking to catch a wave in a hot market,” said Chris Lynch, Partner at Accomplice (formerly Atlas Venture). “DataRobot’s rapid ascent is a strong signal that machine learning has advanced from an elite technology to a powerful and differentiating business application.”
“Intel Capital is focused on building technology ecosystems by investing in transformative entrepreneurs and game-changing technologies,” said Ron Kasabian, Vice President of Intel Corp’s Data Center Group and General Manager of Big Data Solutions. “DataRobot’s team of experts and machine learning platform is a great example of a company that is driving innovation in data science.”
DataRobot provides a high performance machine learning automation software platform and an innovative practical data science education program that work together to provide the fastest path to data science success for organizations of all sizes. For more information, visit www.datarobot.com
As information piles up, the demand for expert data analysis heats up
This article is part of the upcoming Top Places to Work issue. The names of the companies that made this year’s list will be released online Thursday night.
Jeremy Achin remembers the day when his social network started filling up with people calling themselves data scientists. It was late 2012, shortly after Achin launched DataRobot and Harvard Business Review had just published a 3,000-word report under the headline “Data Scientist: The Sexiest Job of the 21st Century.”
“I saw a lot of people on LinkedIn changing their titles to data scientists — like, rapidly,” Achin says. “But it’s clear that some of these people are not data scientists and can’t actually do the job.”
Who could blame them for posing? Data science is not only sexy (apparently) but also financially rewarding. The annual median salary is $124,150, according to the employment tracking firm CareerCast.
That’s a darn good wage for a profession that didn’t even exist a decade ago. But as companies across many business sectors amass piles of information — big data, in techspeak — they desperately need analytical minds to make sense of it. Combining statistical know-how, computer programming skills, and real-world sensibilities, that’s what data scientists do.
At Boston’s Whoop, for instance, data scientists use biometrics collected by the company’s wristbands to tell athletes whether they are overtraining or undertraining, how much sleep they need, and when their bodies are fully recovered from workouts.
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“What you can do is collect massive amounts of data from people, and patterns will start to emerge that show what can increase your chance of winning and decrease your chance of injury,” says John Capodilupo, Whoop’s chief technology officer.
Meanwhile, the data scientists at EverQuote of Cambridge crunch numbers to help auto insurance shoppers find the best policies for their vehicles — whether customers know what’s best or not. “For a data scientist, the job is to figure out the difference between what people say they want and what they really want,” says Hanlu Li, EverQuote’s vice president of business intelligence.
As Achin suggests, people with complete data science tool kits are harder to find than their online profiles might indicate. “It’s a hybrid role,” says Michael Schmidt, chief executive of Nutonian, a software firm in Somerville. “You need to be able to program and at the same time connect what you find back to the business. It’s pretty rare.”