The job market for data scientists is more active than ever and on track for rapid growth over the next few years. The U.S. Bureau of Labor Statistics predicts that the number of available positions will rise about 28% through 2026.

Companies are investing significant amounts of money into market research and business analysis, creating new opportunities for long-time data scientists and those new to the field. At the same time, the job market is also becoming more competitive. The average compensation for data science positions is rising as these jobs become more important to businesses, encouraging hiring managers to more carefully vet new hires.

Data scientists wanting to stay competitive or break into the field will need the right approach. These techniques will help them search for and secure a new position.

The State of the Global Data Science Job Market

 
 
People are generating more information than ever — experts believe worldwide data is on track to be in excess of 175 zettabytes by 2025. At the same time, innovations in AI and big data analysis have made large data sets more valuable than ever for businesses — but only if they work with trained scientists who can uncover the necessary insights.

Half of all surveyed businesses have used AI in one way or another, and more say they plan to invest further in data-driven solutions in the near future.

Right now, it’s not unusual for a single data science job posting to receive hundreds of applications. Higher demand also means rising compensation, and businesses are being more careful in who they hire for these positions.

In response, many hiring managers are inflating the job requirements of new data science openings — demanding stronger credentials, more experience and additional keywords. Even data scientists with good qualifications or strong academic track records aren’t guaranteed a position right now.

Best Practices for Becoming Competitive in the Global Job Market

 
Data scientists who want to break into the field or secure a new position will need the right strategy to succeed. These six tips will help established professionals and those new to the industry secure work.

1. Know the Right Words to Use

 
Familiarity with popular industry keywords — like Python, SQL, AI and data analytics — can help you write a CV and resume that will more effectively communicate your skill set and get past the resume filters often used by hiring managers.

Keeping up with changing industry demands can also help keep you competitive. While Python remains an essential skill, more businesses expect familiarity with deep learning, gradient boosting machines and big data analytics. Many companies also expect applicants to have used a wide variety of approaches for data mining and analysis in the past.

2. Communicate Familiarity With Industry-Standard Tools

 
When applying for positions that expect knowledge of artificial intelligence, emphasizing knowledge in data science and machine learning may help you secure an interview.

At the same time, keyword stuffing, the act of unnaturally filling a resume with keywords to beat resume scanners or attract the attention of hiring managers, should be avoided. Try to only employ them in a resume or CV when they are relevant and help you explain your unique background and data science skill set.

3. Learn How Big Businesses Look for Data Science Professionals

 
Examining how major companies hire data scientists can also help you improve your resume and CV. AI and ML company Daitaku was recently featured in a case study about how it finds data scientists internationally. The report emphasizes how skill sets matter more than geography.

4. Take Advantage of General Job-Seeking Best Practices

 
Job application best practices typically also help data scientists looking for a new position. Tailoring your CV and cover letter to each job you apply for will take some extra effort. Still, it can help you communicate your particular skill set before an interview and illustrate how you’re a good fit for a certain position.

5. Network With Other Data Scientists

 
Actively networking with other data scientists and recruiters looking for professionals can help you expand your network and more easily find openings that match your skills and experience level.

While waiting to hear back from hiring managers, you may also look for short-term work that can help you further develop your skills and add a bullet point or two to your resume.

6. Consider Freelance Work

 
Businesses needing data scientists but struggling to fill new positions might offer temporary and freelance work to qualified applicants. Platforms like UpWork and freelance job search boards can provide you with leads on these positions.

Looking Forward: How Data Scientists Can Stay Competitive

 
 
There are more openings for data scientists than ever, but that doesn’t mean the market is becoming less competitive. The growing value of data science and the lack of skilled candidates has companies hiring very carefully.

Data scientists wanting to find a new position or break into the market should keep on top of industry trends and become familiar with various mining and analysis techniques. Best practices for job searching — like customized CVs and careful use of keywords — can also help them secure an interview.

You can stand out amid a sea of competitors and land your ideal data science job by employing these techniques.

 
Bio: Devin Partida is a big data and technology writer, as well as the Editor-in-Chief of ReHack.com

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