Dr. DJ Patil, the White House’s first chief data scientist, is a Silicon Valley veteran but no stranger to Washington. (Jabin Botsford/The Washington Post)

The White House’s top data nerd was kicked out of an algebra class in high school and almost didn’t graduate.

DJ Patil, who was named the nation’s first chief data scientist last month, shares credit for coining the term “data science.” He is the latest Silicon Valley transplant to join the Obama administration, working under former Google executive Megan Smith, the White House’s chief technology officer.

At the Office of Science and Technology Policy, Patil shares a work space with former Twitter executive Alex Macgillivray, a skateboard, and a giant Pokemon stuffed toy. He occasionally rides the skateboard to work, and he calls the executive mansion a place filled with “awesomeness.” He says he misses California weather and his favorite Indian restaurants.

But Patil is no stranger to Washington. After graduating from high school in Cupertino, (thanks to “a very kind administrator who took pity on me,” he said in a speech) he went on to obtain a doctorate in applied mathematics from the University of Maryland at College Park. He also had a brief stint at the Pentagon in 2004, analyzing social networks to study emerging threats.

Since then, Patil has worked at LinkedIn, Skype, PayPal and eBay. Most recently, he was an executive at the data intelligence company RelateIQ, which was acquired by Salesforce last year.

In an interview, Patil outlined his priorities as chief data scientist and explained why he made the switch to public service. The conversation has been edited for length and clarity.

Q. What does the first chief data scientist do?

A. To me, the government says, “Okay, we have data, but how do we use that responsibly to create efficiencies, to create transparency, to unlock economic potential? How do we get that data to preserve American competitiveness and advance innovation?”

The mission of this role is an amplification of things that have been happening.

How will you achieve those goals?

There are three areas where we have the biggest chance to succeed in our mission.

The first is precision medicine.

We’re at this place where we have much more comprehensive ways of looking at our bodies. How do we take bioinformatics and what we’ve been able to do in data science and bring them together to optimize health care? The open question is: How do we make precision medicine scalable? How do we bring it to the masses?

The next one is open data. We’ve got data.gov [a Web site that features machine-readable government data], which has really changed the game. Think about the billions of dollars that rest on open data infrastructure. People do research on that data, that research turns into insight, that insight turns into wisdom and that wisdom is put back into models and scientific results. The foundation of all this is open data. How do we enhance that across-the-board?

The third area is tech talent. How do we increasingly bring in and train the necessary talent to prepare our government to capi­tal­ize on open data?

What about the privacy concerns with big data, especially in areas such as precision medicine?

A big part of the framing of precision medicine is how do we do this responsibly?

This is one area where we’re well ahead of the problem, as opposed to the kind of thing that would go on for years and then we’d say, “Uh-oh, we better think about this” when a crisis happens.

Privacy is essential, but there’s also the question of bioethics — the issue of what is the acceptable use of that data. There’s a whole rich field within bioinformatics on the ethical use of data and genetics. The National Institutes of Health has been a leader in this space.

Why did you decide to join government instead of solving the same problems at a technology company?

Given the field of data science and the things we can do, we’re in a really unique place in time and history. When else can you have this kind of impact?

You can go and build an app, and I’ve been fortunate to work on a lot of great technologies. But in this type of role, you get to ask yourself a true-north question every morning.

That question is: Will this impact my kids or my friends’ kids? Will it make their lives better? Will it make their kids’ kids’ lives better?

I don’t really know how you can think about those questions — with that level of focus — as a company. That is, by definition, public service. And once you get a taste of doing public service, it’s really hard to let go.

What’s different about working in Washington now?

Being here 11 years ago versus now — I can’t express how much has changed. Oftentimes, we look at government and say, “Look at that slow-moving ship.”

If anything, it’s really incredible how much change is happening, how much opportunity is there. It’s hard for me to have ever imagined an administration doing this much to empower data science, given that it’s such a new area.

Not only is this the most data-driven organization we’ve seen, but when you look at the demographics of the teams, and how balanced and diverse they are, it’s amazing.

Government in many ways is ahead of a lot of corporations, and I say that coming from industry.

Are there any downsides to the job?

There are always challenges. It’s not supposed to be easy. There are very hard questions to answer. What has been the most impressive thing is the willingness for everyone to roll up their sleeves and get to work.

There’s plenty of days where it’s tough, but I haven’t had a single day where I’ve been demoralized or where I feel like I’m frustrated and I should just pack up shop and head home.