With lots of job openings in the field, data scientists can increase their chances of landing at a great company by updating their online resumes.
The job market for data scientists is wide open, with an estimated 700,000 job openings in the field by 2020, according to an IBM report. And these professionals are in great demand: Nearly 90% of data scientists said they are contacted at least once a month for new job opportunities, while more than 50% said they are contacted on a weekly basis, according to a report from CrowdFlower.
"The demand for data scientists has continued to grow over the past few years years as companies across all industries continue to integrate new technology into core business operations to meet evolving customer expectations," said Sarah Stoddard, community expert at job search site Glassdoor.
It's typical for companies outside of the tech industry to have a strong digital presence and gather large amounts of online data, presenting the need for employees with the ability to collect, organize and analyze this information to help educate business decisions, Stoddard said.
In October, Glassdoor's Local Pay Reports found pay for data scientists had increased year-over-year by 0.9%, to $96,441--an indicator of increasing demand and a way for employers to attract top talent, Stoddard said.
SEE: Job description: Data scientist (Tech Pro Research)
When job seeking, "the most important thing is letting employers know you're out there," said Felix Fermin, a recruiting manager at Mondo. LinkedIn has a feature wherein you can alert recruiters that you are open to opportunities without letting your current employer know that you are looking elsewhere, he said.
Are you looking for a job in data science? Here are three tips for how to improve your LinkedIn profile and attract the most desirable employers.
1. What languages you work in
The top three most in-demand skills for data scientists are Python, R, and SQL, according to recent Glassdoor research. "If you are familiar with these languages, highlighting these abilities in your resume and online career profiles could potentially attract a wider range of employers looking for data science talent, even if you aren't necessarily in the market for a new job," Stoddard said.
Nine out of every 10 data science job postings on Glassdoor require at least Python, R, and/or SQL skills, Glassdoor found.
On Indeed Prime, candidates with specific skills or experience in machine learning, Hadoop, Python, and Java get the most interest from employers, according to Shu Wu, director of Indeed Prime.
"Explaining how you're analyzing the data and what tools you're using on your resume goes a long way," Fermin added.
2. What you're actually doing in your current role
"A lot of people say 'I'm a data scientist at this company,' and that's it," Fermin said. "It doesn't have to read like a resume, but a few sentences about what they're working on, and the why and how of what they're doing greatly improves the ability for employers and recruiters to see what they're doing."
SEE: Here are the 3 top careers in data science, and how much they pay (TechRepublic)
3. Clear examples of how you have mastered data skills
While formal education is important and encouraged, your related data science experience and how you quantify success will be most attractive to employers because they want to understand what expertise you will bring to the table, and how you have helped inform business decisions in the past, Stoddard said.
"Data science roles are constantly evolving with new technologies, so by including clear, quantifiable examples of how you have mastered core related skills and have learned new languages, this will help you stand out among the crowd," she added.
In general, all data scientists should have SQL, statistics, and data/business analysis experience, Wu said. They should also be able to highlight how their skills have impacted overall business.
Job seekers across industries should determine what factors are most important to their happiness and success at a new job. The three top factors that impact long-term employee satisfaction at a workplace include culture and values, career opportunities, and trust in senior leadership. "While these may not be as intriguing as a higher salary during initial negotiations, high marks in these categories could mean the difference between you finding a job that fits your life, and not," Stoddard said.
- Learn these 3 languages now if you want to become a data scientist (TechRepublic)
- Analytics and data jobs: What employers are looking for (ZDNet)
- Report: 59% of employed data scientists learned skills on their own or via a MOOC (TechRepublic)
- How to build a data science team (ZDNet)
- How to build a successful data scientist career (free PDF) (TechRepublic)