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New Hiring Formula Values Math Pros

Being a math geek has never been cooler, at least in Silicon Valley.

As Bay Area technology companies ramp up hiring out of the recession, they are in hot pursuit of a particular kind of employee: those with experience in statistics and other data-manipulation techniques.

Rather than looking for just plain-vanilla computer scientists, who typically don't have as deep a study of math and statistics, companies from Facebook Inc. to online advertising company AdMob Inc. say they need more workers with stronger backgrounds in statistics and a related field called machine learning, which involves writing algorithms that get smarter over time by looking for patterns in large data sets.

That is leading to opportunities for quantitative specialists like Andrés de Lucca. The 30-year-old, who graduated from Northwestern University's Kellogg School of Management with a concentration in analytical consulting in 2009, says he found himself sought after by some major technology companies. He was hired by Social Gaming Network Inc., a Palo Alto online videogame maker, late last year.

At SGN, Mr. de Lucca now manages a three-person team that studies game-play data, such as how long people spend in certain parts of a videogame, to detect areas to improve. For example, by contrasting various missions of SGN's "Skies of Glory" fighter pilot game, Mr. de Lucca and his group found that people were quitting when the game was too easy rather than too hard.

"Some patterns aren't as obvious as they seem," says Mr. de Lucca. Using the findings, SGN gradually increased the game's difficulty, getting people to play it longer and spend more on virtual goods inside of the game, he says.

The focus on math aces like Mr. de Lucca shows how Silicon Valley tech companies, which have long been data-minded, are now becoming obsessively so. Cloud computing, the process of storing data remotely rather than on a company's own equipment, is allowing firms to keep more data than ever by lowering the costs of handling it. Companies can then use the data they gather to refine services, especially online, as soon as they detect a pattern.

Now as local high-tech companies step up hiring, many are targeting data-expert specialists to gain a leg up over competitors. Michael Morell, managing partner at Riviera Partners in San Francisco, says the recruiting firm has seen more companies seeking to build data-analysis and data-warehousing teams. "They're putting a massive emphasis on it," he says.

Riviera is working to find quantitative experts for a gaming company and an online software company that want to build "internal centers of excellence" around data, Mr. Morell says. He says those with strong statistics backgrounds will earn up to 20% more than generalist engineers, who typically start with salaries in the low six figures.

The most desirable candidates, employers say, can have a variety of experience and educational backgrounds. Companies say specific degrees are less important than a focus on data-mining techniques.

Mike Schroepfer, Facebook's vice president of engineering, says the social-networking company has a growing need for employees with statistics backgrounds. "When you build for the Web, you have quicker real-time access about how people are using the product," he says. "You have to use the data in the proper way."

The company is tackling the problem in two ways. In the summer of 2008, it created a six-week-long boot camp required for all new engineers and included a module on training in probability and statistics. Employees teach new recruits to use tools for comparing the performance of one version of a feature with another and how to determine what sort of difference in response is meaningful.

Secondly, Mr. Schroepfer says the company has been hiring more people for its data science group, its SWAT team of fewer than 20 Ph.D.s with the deep background to analyze sample sets of terabytes of data, looking for patterns that could help optimize products and ads.

Local universities are trying to bulk up the supply of graduates with deep quantitative backgrounds. Stanford University, one of the largest feeders of engineers into Bay Area tech companies, began requiring its computer-science undergraduates to take a specialized course in probability two years ago. Enrollment in a more-advanced version of the class also has been growing steadily, drawing 260 students in 2009, up from 215 in 2008, says Mehran Sahami, a Stanford associate professor of computer science.

"Interest mirrors industry," says Mr. Sahami, who was previously a senior research scientist at Google Inc. He says that among other things, the courses teach students to build applications that can predict whether a patient might have a heart abnormality based on X-ray data and to understand how email spam filters work.

Write to Jessica E. Vascellaro at

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