Many popular tools for analyzing data require programming (R, Hadoop,
Pandas, Spark, etc.) and many data scientists know how to write code.
But many data scientists also use graphical tools (like Excel or
Tableau) to explore data. Is it possible to be a great data scientist
if you can’t code? If it’s not possible today, are there tools that
could make it possible?
In this Oxford Style debate, two teams of the world’s best data
scientists will debate the following proposition: “If you can’t code,
you can’t be a data scientist.” We’ll feature a mix of questions from
the moderator, and questions from the audience, and ask for the
audience’s help in determining the winning team.
Preliminary list of debaters:
- Roger Magoulas
On the “agree” side:
- Lucian Lita
- Hilary Mason
On the “disagree” side:
- Joseph Adler
- Scott Nicholson
Joseph Adler has many years of experience in data mining and data analysis at companies including LinkedIn, DoubleClick, American Express, and VeriSign. He graduated from MIT with an B.Sc. and M.Eng in Computer Science and Electrical Engineering. He is the inventor of several patents for computer security and cryptography, and the author of “Baseball Hacks” and “R in a Nutshell”. Currently, he is head of product at Interana, a stealth startup in Palo Alto.
Hilary Mason is the Chief Scientist at bit.ly, where she finds sense in vast data sets. Her work involves both pure research and development of product-focused features.
She’s also a co-founder of HackNY, a non-profit organization that connects talented student hackers from around the world with startups in NYC.
She has discovered two new species, loves to bake cookies, and asks way too many questions.
Scott Nicholson most recently was Chief Data Scientist at Accretive Health, where his team built out data infrastructure, predictive analytics and data visualizations to help healthcare providers make better clinical and financial decisions. Before moving into the health care industry Scott was a Team Lead, Senior Data Scientist and Economist at LinkedIn where his work focused on using analytics and prototyping new data products to increase user engagement. Earlier in his career, Scott built real-time bidding and ad selection algorithms at an online advertising startup. He has a BS in Economics/Mathematics from the University of California, Santa Barbara, and an Economics PhD from Stanford.
Director of data engineering at Intuit. Previously, founder of Level Up Analytics, lead analytics and engineering team at BlueKai, PhD in computer science from Carnegie Mellon
Roger Magoulas is the director of market research at O’Reilly Media. Magoulas runs a team that is building an open source analysis infrastucture and provides analysis services, including technology trend analysis, to business decision-makers at O’Reilly and beyond. In previous incarnations, Magoulas designed and implemented data warehouse projects for organizations ranging from the San Francisco Opera to the Alberta Motor Club.
Comments on this page are now closed.