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It’s the job the Harvard Business Review has called “the sexiest job of the 21st century”. Is it modeling? Pro sports? Nope. It’s data science. Over the past decade, as the tech world has seen advances in big data, machine learning, cloud computing, and artificial intelligence, opportunities for data scientists have blossomed. In addition, their compensation has blossomed as companies increasingly demand data scientists. How do you become a data scientist, and how do you get hired? Here we break down the basics for you.
While we often hear astronomically high figures for data scientist salaries and may feel compelled to jump into the profession simply on that account, it’s important to first evaluate whether this profession really suits your skills and strengths. Data science involves — almost exclusively — heavy computation, math, and computer programming, day in and day out. Consider taking an online course on data science before delving into degrees and training programs.
Your first step towards becoming a data scientist is earning a bachelor’s degree. Data scientists hail from a variety of undergraduate disciplines within the field of STEM, including statistics, engineering, math, computer science, and physics. While further education isn’t technically required to enter the data science field, the vast majority of data scientists hold advanced degrees, including 44 percent who hold a master’s degree and 48 percent who hold PhDs. Gaining an advanced degree can also give you an edge in the job market by offering you the opportunity to specialize in a particular field of data science, such as data visualization, database management, cloud computing, or machine learning.
Becoming a data scientist is all about technical skills. While soft skills like communication, diligence, and organization are certainly important for a data science role, the bulk of the work you’ll be doing as a data scientist requires some serious technical skills, including knowledge of programming languages, data analysis software, statistical methods, and practical knowledge of data analysis implementation.
Opportunities for data scientists are available in many areas, including the tech industry, related industries that use technology, government research, and academic research posts. In the private sector, the hiring process as a data scientist requires candidates to put their hard skills and soft skills on display. Like any application, you’ll most likely submit a resume and cover letter to the company you’re interested in, or a recruiter will reach out to you. You may also be asked to show previous examples of your work as a data scientist.
If the company likes your resume, they may set up an interview right away, or they may send you a pre-screening assignment first. Once candidates reach the interview stage, two types of interviews should be expected: an interview to assess fit with the company culture, previous work experience, and soft skills, and a technical interview to assess the candidate’s mathematics, data analysis, and coding abilities. Depending on the level of the position you’re applying for, there may be additional take-home assignments and interviews with company personnel to assess the candidate’s fit for the role.
As with most professions, salaries for data scientists vary widely based on his or her years of experience. Salary data from Glassdoor indicates that the average base pay for data scientists is $117,345 yearly, and the average base pay for senior data scientists is $136,633 yearly. An entry level data scientist can expect to make $99,834, on average according to Glassdoor salary data. Meanwhile, a seasoned veteran can earn above $141,921 on average, with companies like Facebook, Google, Booz Allen Hamilton, IBM, and Oracle paying more.
According to the Bureau of Labor Statistics, there were 27,900 computer and information research scientists employed in the United States in 2016. The BLS projects that from 2016 to 2026, employment for computer and information research scientists will grow by 19%, which is much higher than the average for other professions.
Data Scientist has consistently been ranked one of the top 50 Jobs in America, according to Glassdoor, with a high job satisfaction rating as well as a high median base salary.
“There’s no question that emerging technologies designed to grow and scale business, such as artificial intelligence, machine learning and automation are having an impact on the types of jobs employers are hiring for across the country. As a result, we’re seeing a spike in demand for highly-skilled workers,” said Glassdoor Economic Research Analyst Amanda Stansell.
Preparing for data scientist interviews can be a gargantuan task. Not only do you have to talk to interviewers about your past experience, work philosophy, and strengths as an employee, you also need to prove your technical prowess through grueling take-home assignments and in-person technical interviews. Here are a few tips for preparing for your data science interview:
There are many careers besides being a data scientist that allow you to get hands-on with data and work within the technology industry. For the careers below, there are ample opportunities in the technology industry with high compensation, and only a Bachelor’s degree is required – or, if you’re highly motivated, self-training on the skills necessary.
Median Pay: $103,560
Degrees Required: Bachelor’s degree
Median Pay: $87,020
Degrees Required: Bachelor’s degree
Median Pay: $67,990
Degrees Required: Associate’s degree