Data scientists have hit the big time. We know this because The White House is hiring one.

Dhanurjay “DJ” Patil was recently named the White House’s first data scientist—his official title is Chief Data Scientist and Deputy Chief Technology Officer for Policy at the White House. Patil will report to Federal CTO Megan Smith (formerly of Google), but will also work with the new Federal CIO, Tony Scott (formerly of VMWare), and the U.S. Digital Service, which will be expanding to 25 more agencies this year.

“How do we build an ecosystem of data products that add value?” Patil reportedly asked attendees at the Strata + Hadoop World conference in San Jose shortly after his appointment. “Let’s start bringing the data science and bioinformatics together, let’s start building those products that showcase the value proposition, not just opening the data.”

Patil, an Indian-American, most recently served as the Vice President of Product at RelateIQ, which was acquired by Salesforce. He also previously held positions at LinkedIn, Greylock Partners, Skype, PayPal, and eBay. (If you’ve used LinkedIn’s “People You May Know” feature, you’ve used some of his work, writes the Wall Street Journal.) Before that, he worked at the Department of Defense, where he directed new efforts to bridge computational and social sciences in fields such as social network analysis to help anticipate emerging threats to the United States.

“There is arguably no one better suited to help the country better embrace the relatively new discipline of data science than Patil,” writes Jessi Hempel in Wired. “He is often credited with coining the term. In 2012, he co-authored the Harvard Business Review article that called out ‘data scientist’ as the sexiest job of the 21st century. At the time, he was the data-scientist-in-residence at Greylock Partners, where he shared with me his life’s mantra: ‘If you can’t measure it, you can’t fix it.’”

Patil says his mission is to “responsibly source, process, and leverage data in a timely fashion to enable transparency, provide security, and foster innovation for the benefit of the American public, in order to maximize the nation’s return on its investment in data.” Which is pretty high-level, but he goes on to focus on four areas:

  • Maximizing social return on federal data
  • Creating nationwide data policies that enable shared services and forward-leaning practices to advance our nation’s leadership in the data age
  • Working with agencies to establish best practices for data management and ensure long-term sustainability of databases
  • Recruiting and retaining the best minds in data science for public service to address these data science objectives and act as conduits among the government, academia, and industry

Patil said he plans to work primarily in areas such as “precision medicine,” which means medicine focused on an individual’s genetics, environment, and lifestyle; more usable open data; and protecting privacy and working ethically with the data.

Needless to say, plenty of other people have ideas about what Patil should be doing. “If I were to draw up this chief data scientist role at least 50 percent of the job would have this person riding shotgun with the General Accountability Office,” writes Larry Dignan in ZDNet. “These two could be the Batman and Robin of budget ball busting and efficiency.”

In particular, Dignan thinks Patil (whom he characterizes as a “great hire”) should be setting up a data lake, using predictive game theory to figure out how U.S. government actions today will affect the future, making Obamacare more efficient, and making data visualization easier for government employees to use.

Patil has a big job ahead of him because the various federal agencies have, to put it kindly, an uneven reputation in data science, writes Neal Ungerleider in Fast Company. “Despite the increasing importance of analytics and data science for everything from health care to energy utilities to infrastructure to budgeting, analytics policies vary wildly from agency to agency,” he writes. “While some organizations such as the National Institutes of Health, the Department of Defense, and the Department of Energy have been enthusiastic adopters of large-scale data-crunching platforms, other agencies are struggling to integrate data science into their workflow for reasons ranging from organizational culture to extremely limited budgets.”

The clock is ticking on how much time Patil has to figure out this big job, as Obama only has 22 months until his presidency ends.

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