Several data scientists have left LinkedIn following a reorganization earlier this year. Now they’ve gone off in a bunch of directions — but one of the main beneficiaries of the exodus is none other than

The cloud software provider has hired four one-time LinkedIn data scientists in the past few months: Vitaly Gordon, Leah McGuire, Sal Uryasev, and Ahmet Bugdayci. A startup called Timeful has also netted some data science talent from LinkedIn, picking up Gloria Lau, Joyce Wang, and Zachary Cain. But there’s a deeper story to tell about Salesforce.

In the past few years, social networks like Facebook and Twitter represented good places for data scientists to go after their tours of duty at LinkedIn. But all sorts of companies have reasons to hire data scientists, who can analyze usage and develop new products and features that rely heavily on available data. The new hires show that Salesforce is becoming more serious about building up its ability to make the most of the data it already has on hand.

Salesforce declined to comment for this story.

The $392 million acquisition of RelateIQ in July is one sign Salesforce has data on the brain. The startup figured out ways to take information from calendars, email inboxes, and phone call logs and update records on how salespeople were doing in terms of working with leads and existing customers. The technology automates processes that normally take time for people to do. Small wonder that Salesforce, a major vendor of customer relationship management software, was interested.

But Salesforce didn’t only get smart software out of the acquisition. It also picked up some great talent, including former LinkedIn employees like Ruslan Belkin, Richard Park, and DJ Patil. Patil in particular is notable; he’s credited with co-coining the term data scientist.

And Salesforce isn’t done hiring. The company recently hired a director for the Data Science Lab inside its product intelligence team and is hiring data scientists as well as people to support them. According to a job listing for a senior data scientist position inside the lab, people who work there “are tasked with surfacing hidden relationships in our data, offering actionable metrics for decision-making, and turning seemingly unrelated ideas into powerful insights by leveraging advanced statistics, data mining and machine learning.”

All of this suggests Salesforce wants to win data science mindshare — or at least prevent competitors from acquiring considerable talent. Time will tell, though, how much these people will be able to improve Salesforce’s current products or affect the company’s long-term trajectory.

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