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How to Land a Job in One of the Fastest Growing Industries

When was the last time you picked up your phone and scrolled through your Instagram feed? Checked out a story on Snapchat? Bought something from Amazon?

Well, what you might not have realized is the driver of every one of those applications is data.

And, in order to stay relevant, companies are using said data to predict what will be the next big thing. The people at the center of all that action? Data scientists.

So, it’s no wonder that a 2012 report in the Harvard Business Review dubbed the profession “the sexiest job of the 21st century.”

It is forecasted that demand for data scientists will soar by 28% by 2020, as companies collect data from a wide variety of sources and need to analyze them to provide better outcomes: clicks online, household water meters, food shopping purchases, health records. But, simply gathering data isn’t enough. Somebody needs to make sense of all those numbers and find patterns to work with. Which is what data scientists do, they analyze data for patterns and use history as a predictor for future outcomes.

So, now that we’re clear on what a data scientist does and how sexy it is, how do you become one?

Must Love Data

It might sound obvious, but to be a data scientist, you have to love data, says Mary L., Data Scientist at New York Life. Mary was always good at math and admits she was “basically married to the math department” in high school.

Jeremy B., from New York Life’s Enterprise Data Management team, says his passion for data started when he began predicting problems in a prior company’s platform so that issues could be fixed proactively.

While Mary appreciates that her colleagues are from different cultures and training backgrounds from financial mathematics to actuarial science, they are all united by their love of data. Mary herself was a statistician long before the term data scientist became popular and she suggests that being comfortable working with data is arguably the most important aspect of the job.

However, Jeremy advises potential would-be data scientists to add programming to their toolset if they can: “there are skills that could be refined and developed around programming, whether that’s [by learning] different languages like Java or Python or even the ability to go through and write standard SQL queries.”

Stand Out in a Crowd

Standing out in a pool of applicants is always a good thing and that holds true for jobs in data science, too.

Jeremy points out that because data science is still a nascent field, there is no standard for what one needs to know to be successful in the industry. “What we’re really looking for is people who are intellectually curious,” he says, “folks who are willing to dig deeper, who continue to want to make themselves and the company better through advances in data technologies.”

At New York Life, for example, since data scientists work with colleagues who have different backgrounds, they bring their own perspectives to the table, which is always valued, Raul H., from the Customer Relationship Management team at New York Life says. At the end of the day, it “comes down to having a passion for data and actually wanting to dig in, pull data sets apart, and really become an expert on the data set that you’re evaluating,” Jeremy adds.

The bottom line: Much like other jobs, you can stand out by showing you’re a team player and are willing to get down in the trenches and get your hands dirty.

“You will be applying your skills and knowledge to help grow the practice. So you will feel ownership and you will be learning at the same time,” Jeremy says, adding that the cutting-edge data science work at New York Life gives it a startup vibe.

Above all, you must have a passion for data. It’s the only way to mold your career in a booming, evolving and yes, sexy, field.

So, whether we’ve convinced you that data science is your dream job or you’re still on the fence, we rounded up some of the most common tech roles (data science included), and how to land them.

Infographic design by Mary Schafrath.