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Lies, Damned Lies, And The Data Scientist
Monica Rogati (LinkedIn)
When it comes to big data insights, how do you know you’re asking the right questions? Hiring data scientists is a good start – we’re seeing their growth both on LinkedIn and at LinkedIn. But even data scientists are not immune from the myriad of hidden pitfalls that keep your key insights out of sight.
Drawing from a deceptively simple exercise that I’ve used to haze dozens of data scientists on their first day, I will discuss the good, the bad and the ugly lessons we’ve learned about asking the right questions, denominators and being a data skeptic.
Video
Monica Rogati
As one of the founding members of the LinkedIn data science team, Monica turns data into products, actionable insights and (news) stories.
Monica obtained her PhD in Computer Science from Carnegie Mellon, where she focused on text mining and applied machine learning. At LinkedIn, she pioneered data driven products with multi-million dollar business impact and is currently building mathematical models that power LinkedIn’s personalized recommendations. When she doesn’t name projects after Harry Potter, Monica finds stories in the LinkedIn data about the most overused buzzwords, trending job titles, entrepreneur DNA, promotion cycles for Millennials and first names that tend to succeed. Her stories appeared in thousands of media outlets – from the Wall Street Journal & The Economist to NPR & CNN to Real Simple & (yes!) Howard Stern.
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©2011, O'Reilly Media, Inc.
(800) 889-8969 or (707) 827-7019
Monday-Friday 7:30am-5pm PT
All trademarks and registered trademarks appearing on oreilly.com are the property of their respective owners.
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