As Hal Varian famously predicted back in 2009, data scientists have seen explosive job-demand in recent years. Even in the face of a global recession, in the last two years, the average salary for data scientists and Hadoop engineers is spiking well over $100k all around the country.
So, how do you build a crack team of data scientists and engineers on a shoestring budget? At Infochimps, we’ve been able to craft a team of data scientists by drawing upon smart, enthusiastic hires from our nearby university in untraditional areas such as non-linear dynamics and statistical physics, and equipping them with the process and tools that accelerate their transformation into bona fide data scientists. Drawing from both his experiences as a teacher and his vast programming and data experience, Flip developed our methodology that embraces failure and constantly pushes people outside of their comfort zone, ultimately resulting in better, smarter scientists.
Our unique approach to data science is well suited for our small, nimble organization. Emphasizing program simplicity and programmer fun over runtime efficiency lets us run the minimum viable experiments that a lean startup requires. Cloud computing and dev ops let us achieve massive horizontally scaling with minimal distraction.
In this 40-minute presentation from the co-founder of Infochimps, Flip Kromer will walk you through our process of recruitment and data science methodology within a fast-paced and pivotal startup. In the end, you’ll learn how to make data scientists out of just about any (smart, driven) simian.
Flip is the Founder and CTO of Infochimps, a data marketplace to find any data-set in the world. He holds a B.S. in Physics and Computer Science from Cornell University and attended graduate school in Physics at the University of Texas at Austin. Flip enjoys riding his bicycle around Austin, eating homemade soup, and playing extreme Scrabble. The idea for Infochimps was inspired by Flip’s abhorrence of redundancy and desire to make the world a happier place for data lovers of all kinds.
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