After a decade as an academic neuroscientist at Harvard and MIT, I got a fellowship to get an MBA at Harvard. It was there that I came up with the idea for pymetrics. Business school is a front-row seat to recruiting for two years. I was shocked to see it really hadn’t changed in the (many) years since I’d graduated from college. My classmates were prepping for 6 months to land their “perfect” internship or job, only to hate it 3 days in. And this was happening for overserved Ivy-league MBA students – I could only imagine what was happening everywhere else. I was also experiencing the problem myself. My 30-page-plus academic resume told me nothing about what I could do in the business world, let alone that I could be a tech entrepreneur. I was a 38-year-old single mom who didn’t fit the 20-something, male entrepreneur mold. I knew that many career swtichers like myself – including those transitioning from the military -- were in the same boat. There had to be a better solution. In the day and age of Netflix, Spotify and Amazon -- platforms that take in information about you and give you personalized recommendations that seem to know you better than you know yourself – where was the equivalent for jobs? Netflix’s movie recommendations are not based on their “back of the movie” blurbs. instead, they analyze movies based on deep analysis of traits and then match you based on the traits you like in movies. So why are we still evaluating people based on their “blurbs,” i.e. their resumes? Why was no one applying this powerful technology to help us make one of our most important decisions – what we do with our careers? pymetrics set out to solve this problem, harnessing the power of the long-tail to match people to the jobs where they are most likely to succeed.