The Noisy Channel


Data Science at LinkedIn: My Team

May 17th, 2012 · 8 Comments · General

Lots of people ask me what it’s like to be a data scientist at LinkedIn. The short answer: it’s awesome. Folks like Pete Skomoroch and team are building data products related to identity and reputation, such as Skills and InMaps. Yael Garten is leading the effort to understand and increase mobile engagement. And other folks work on everything from open-source infrastructure to fraud detection. Amazing people helping our 160M+ members by deriving valuable insights from big data.

I wanted to take a moment to showcase my own team. As a team, we straddle the boundary between science and engineering. We work closely with several engineering teams to deliver products that our members use everyday.

Joseph Adler is a name you might recognize from your bookshelf: he wrote Baseball Hacks and R in a Nutshell, both published by O’Reilly. At LinkedIn, he is a data hacker extraordinaire, currently focused on improving the network update stream.

Ahmet Bugdayci just joined LinkedIn this year, and he’s already on a tear. He’s working on a better approach to representing job titles, one of the most fundamental facets of our members’ professional identity. And he’s a polyglot.

Heyning Cheng is our innovator in chief. He envisions data products and does whatever it takes to hack them together. Our recruiters are especially happy to be his beta testers, and we’re working to turn those prototypes into shipped product.

Abhimanyu Lad is working on the next generation of LinkedIn search. He’s already improved spelling correction and group search, as well as building better ways to measure search effectiveness. But stay tuned — the best is yet to come!

Gloria Lau leads all things data for the student initiative. Check out LinkedIn Alumni to see what she’s been up to. Students are the future, and we’re excited to be making LinkedIn a great tools for students, alumni, and universities.

Monica Rogati spearheaded many of LinkedIn’s key products: the Talent Match system that matches jobs to candidates; the first machine learning model for People You May Know; and the first version of Groups You May Like. When she’s not working on our products, she gives awesome presentations.

Daria Sorokina recently joined us and is working on search quality. She’s a hard-core machine learning researcher and developer: check out her open-source code for additive groves.

Ramesh Subramonian has been focused on data efforts for our international expansion. Over 60% of our members live outside the United States, and his efforts ensure that LinkedIn’s value proposition is a global one.

Joyce Wang is a data science generalist. She is part of the search team, but she’s built great tools for log analysis and human evaluation that are finding great use across the company.

I hope that gives you a flavor of what it’s like to be a data scientist at LinkedIn — and on my team in particular.

Do you possess that rare combination of computer science background, technical skill, creative problem-solving ability, and product sense? If so, then I’d love to talk with you about opportunities to work on challenging problems with amazing people!

8 responses so far ↓

  • 1 Quora // May 18, 2012 at 10:13 am

    If I want to do Data Science, would LinkedIn or Twitter be a better place to start work?…

    Full disclosure: I lead the Product Analytics data science team at LinkedIn. I can’t speak for Twitter, but I can tell you that my team is as badass as they get. You can look at my bio (MIT -> CMU -> founding team at Endeca -> Google -> LinkedIn) to a…

  • 2 Nic // May 20, 2012 at 9:55 pm


    Sticking to first name only just in case. Do you guys hire people who work remotely but with a willingness to make a pigrimage to Mountain View on a regular basis? Or maybe I should ask this, are all your team based there?



  • 3 Daniel Tunkelang // May 20, 2012 at 10:21 pm

    So far we haven’t tried working with anyone remotely. At our size, it would be pretty tough — especially if only one person on the team were to work remote. Never say never, but our current strategy is to lure people to the utopia that is Silicon Valley. 🙂

  • 4 Profiles in Data Science: Monica Rogati | What's The Big Data? // Jun 14, 2012 at 3:23 pm

    […] Built the LinkedIn product analytics team from 2 to 10 data scientists. Spearheaded many of LinkedIn’s key products: the Talent Match system that matches jobs to candidates; the […]

  • 5 Hiring: Taking It Personally // Aug 1, 2012 at 11:09 pm

    […] taking it personally extends to sourcing. Earlier this week, the LinkedIn data science team hosted a happy hour for folks interested in learning more about us and our work. Of course we used […]

  • 6 The End of a Seven-Year Cycle: Leaving LinkedIn | Diego Basch's Blog // Aug 10, 2012 at 8:33 pm

    […] Pearce’s character in Memento. For example, LinkedIn has unique data about the world of work; one of the best teams of data scientists on the planet (led by my friend Daniel Tunkelang) is doing awesome stuff with it. I look forward to […]

  • 7 Data Werewolves // Aug 23, 2012 at 9:40 pm

    […] to find more data werewolves. Check out my team! Don’t worry, they only bite when they’re hungry. If you enjoyed this post, make sure […]

  • 8 Lily 5.0, LinkedIn 2.0 // Dec 5, 2012 at 11:45 pm

    […] how quickly two years have gone by, and how the team has grown in numbers and accomplishments. My team post from May already feels so dated! I’ll update it in the next few […]

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