This post originally appeared on Mashable.com on behalf of CyberCoders.
Looking to make the biggest bucks in the fastest growing industry?
There are two crystal clear — albeit unsurprising — commonalities among the top 10 highest paying jobs in the tech industry. If you want to cash in the biggest checks, you have to:
Step 1: Become a killer programmer or big data expert.
Step 2: Move to the West Coast.
Most of the highest paying jobs are, naturally, in the root of tech innovation in Silicon Valley. This is also among the most expensive cost-of-living areas in the nation. A few up-and-coming tech hubs, like nearby San Francisco, Seattle and even Silicon Beach down in Southern California made it on the list as well.
Folks who know how to handle, parse and analyze an overwhelming amount of data will get the fattest paychecks in 2015 — three of the five highest paid jobs are centered on big data. We dug into the CyberCoders database of hundreds of thousands of job postings to find the average salaries of technology-related jobs. Here are the highest paying jobs and the cities in which they're located.
Data scientists are some of the most expensive and coveted professionals around today. "It’s important to note that data mining as it relates to data science is not traditionally taught in university-level computer science curricula," says Ray Bao, data scientist at CyberCoders.
While there are new, in-demand programs, like UC Berkley’s Masters of Info and Data Science,
"oftentimes, what is taught in academia pales in complexity to real-world problems,"
"oftentimes, what is taught in academia pales in complexity to real-world problems," Bao says.
So what’s the path to becoming a money-making data science expert? This infographic by Data Camp breaks down the typical background and necessary hard skills: According to the graphic, the core set of skills you need to learn centers heavily on statistics and mastering the appropriate programming tools, including Python and R, as well as database querying language SQL.
But that’s not all; data science requires deep analytical thinking and creativity. Data scientists should be able to not only solve complex problems through data mining but also ask the right questions to extract meaningful conclusions about the data, Bao says.
Bao suggests subscribing to Revolution Analytics to stay abreast of using open source R for big data analysis in addition to browsing Stack Overflow to learn and help other developers.
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