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Presented to the Bay Area Search Meetup on February 26, 2014 http://www.meetup.com/Bay-Area-Search/events/136150622/ At LinkedIn, we face a number of challenges in delivering high quality search results to 277M+ members. Our results are highly personalized, requiring us to build machine-learned relevance models that combine document, query, and user features. And our emphasis on entities (names, c
How To Interview a Data Scientist Daniel Tunkelang Presented at the O'Reilly Strata 2013 Conference Video: https://www.youtube.com/watch?v=gUTuESHKbXI Interviewing data scientists is hard. The tech press sporadically publishes “best” interview questions that are cringe-worthy. At LinkedIn, we put a heavy emphasis on the ability to think through the problems we work on. For example, if someone clai
Keeping It Professional: Relevance, Recommendations, and Reputation at LinkedIn Daniel Tunkelang (LinkedIn) LinkedIn operates the world's largest professional network on the Internet with more than 100 million members in over 200 countries. In order to connect its users to the people, opportunities, and content that best advance their careers, LinkedIn has developed a variety of algorithms that su
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