Editor’s Note: Semil Shah (@semil) is an EIR with Javelin Venture Partners
“In the Studio” kicks off the fall season by hosting a data scientist who, originally trained in mathematics and physics, worked his way through the Valley through a variety of analytics and research engineering positions before landing a spot in one of the consumer web’s most data-driven companies.
Now a Principal Data Scientist at LinkedIn, Peter Skomoroch (pronounced “Ska-ma-rock”) has some views on the craze around the title “data science,” a term that’s been buzzing around the Valley alongside favorites such as “growth hacker” and “social media expert.” In this discussion, Skomoroch articulates what I believe should be the standardized definition for what a true data scientist is within the world of consumer Internet services and applications. Specifically, he believes data scientists are bring together generalist skills in the fields of business intelligence (with some product sense), mathematics and statistics (in order to construct and tune algorithms) and computer science (to write the actual code) to form a “Voltron” of data science.
This short discussion would be of interest to any person in the field who hopes to take a path to become a data scientist, because right now, there aren’t many Voltrons out there…yet. Skomoroch offers tactical advice for those who may be strong in one area and how to get relevant experience in other areas. He also looks back at his own career, one that began with a deep interest in neuroscience in high school, which evolved to math and physics in college, and as he became exposed to industry, took a liking to business applications as well. The result is that Skomoroch is one of small handful of true data scientists at the consumer web level who can combine the advanced statistics with machine learning techniques to help companies build and tune products and services.