The war for analytics talent is tough enough. But imagine competing against the likes of Facebook, LinkedIn and Microsoft for qualified candidates. They’re only a handful of the companies currently looking to hire data scientists and other analytics professionals.
To help bridge this chasm, data analytics veteran Vincent Granville launched AnalyticTalent.com, an online job board for analytics professionals that posts about 200 data-related job listings and hosts 1,500 resumes. He also started AnalyticBridge.com, a social network for analytic professionals with more than 45,000 subscribers.
Granville says that as a group, these data professionals are statisticians who know more than math; they are both business-savvy and technology savvy, and eager to solve important commercial challenges that solve problems and use the latest and greatest IT systems.
While the job board helps match candidates for a range of jobs—business analyst, data analyst, data engineer, data scientist and marketing and sales analytics experts—with an array of companies, Granville says a carefully crafted job posting can make the difference between an opening that attracts applicants and one that flies under candidates’ radar.
“You always hear how it’s impossible to find data science candidates but the talent is out there,” says Granville. Here’s how he says companies can design an analytics job posting that taps into this talent pool:
1. Make the job about business.
Data scientist candidates and other analytics professionals are looking for opportunities to share their business acumen and partner with line-of-business leaders. “Twenty years ago, a data geek would work alone and with very little interaction with other people. But that’s changed,” says Granville. “Data scientists now want to be able to interact with finance, marketing, the product department, sales reps and clients. Sure, they’re still the guys with strong computer science and statistical backgrounds but they also have business expertise.”
2. Embrace big data challenges.
The best analytics professionals are known for loving a challenge. That’s all the more reason to craft a job posting that describes some of the more challenging problems involving big data that new hires will be expected to tackle. While competitive reasons might discourage companies from including too many project details in a job posting, Granville says hinting at the opportunity to use programming models that involve massive datasets such as MapReduce is often enough of a clue to entice job seekers. Also worth mentioning: the chance to “analyze data coming out of social networks and anything that’s related to mobile analytics,” says Granville.
3. Make the job easy to find.
Every online job seeker’s search for a position begins with entering a keyword. The challenge, however, is making sure your job posting features the keywords that data scientists are most likely to try. According to Granville, buzzwords such as “big data, predictive analytics, predictive modeling and business analytics” are essential. At the same time the market is trending toward “project manager” and “systems analyst.” “Words that were once more traditionally connected with software engineers are now becoming more popular within the framework of data science,” he adds.
As for those words that are falling out of favor: Granville says terms like “statistician” and “time series” are fast losing popularity and would be best left off the list.
4. Speak the right programming language.
It pays to include programming prerequisites in analysts’ job descriptions—particularly the statistical programming language R which allows users to perform complex data analysis in an open source environment. “Sixty to seventy percent of data-related positions now request familiarity with statistical programming languages like R,” says Granville.
He adds there is plenty of room for other programming languages, such as Perl, C++ and Java which remain popular among analytics experts. Candidates also should demonstrate expertise with SQL and NoSQL database management systems.
P.S. About the Money
Job descriptions posted online, whether they are at a company website or at a jobs board, usually don’t mention compensation specifics. And while it takes more than money to land an analytics professional, a highly competitive salary certainly doesn’t hurt.
According to a recent survey conducted by business intelligence company SiSense, the annual earnings of a data professional can range from an average of $55,000 for a data analyst to an average of $132,000 for a vice president of analytics. What’s more, almost 80 percent reported that they expected a salary increase in 2013. Important information to keep in mind when adding a salary range to a job posting.
Cindy Waxer is a Toronto-based freelance journalist and a contributor to publications including The Economist and MIT Technology Review. She can be reached at firstname.lastname@example.org or via Twitter @Cwaxer.