Presented By O'Reilly and Cloudera
Make Data Work
March 28–29, 2016: Training
March 29–31, 2016: Conference
San Jose, CA
Daniel Tunkelang

Daniel Tunkelang
Advisor, Various

Website | @dtunkelang

Daniel Tunkelang is a data science and engineering executive who has built and led some of the strongest teams in the software industry. He was a founding employee and chief scientist of Endeca, a search pioneer that Oracle acquired for $1.1B. He led a local search team at Google. He was a director of data science and engineering at LinkedIn, and he established their query understanding team. Daniel also advises and consults for companies that can benefit strategically from his expertise. His clients range from early-stage startups to “unicorn” technology companies like Etsy and Flipkart. He helps companies make decisions around algorithms, technology, product strategy, hiring, and organizational structure.

Daniel is a widely recognized writer and speaker. He is frequently invited to speak at academic and industry conferences, particularly in the areas of information retrieval, web science, and data science. He has written the definitive textbook on faceted search (now a standard for ecommerce sites), established an annual symposium on human-computer interaction and information retrieval, and authored 24 US patents. His social media posts have attracted over a million page views. Daniel studied computer science and math at MIT and has a PhD in computer science from CMU.

Sessions

5:10pm–5:50pm Wednesday, 03/30/2016
Moderated by:
Michael Dauber (Amplify Partners)
Panelists:
Yael Garten (LinkedIn), Monica Rogati (Data Natives), Daniel Tunkelang (Various)
Average rating: ****.
(4.14, 7 ratings)
We’ve all heard that rare breed the data scientist described as a unicorn. In building your DS team, should you hold out for that unicorn or create groups of specialists who can work together? Michael Dauber, Yael Garten, Monica Rogati, and Daniel Tunkelang discuss the pros and cons of various team models to help you decide what works best for your particular situation and organization. Read more.