Never. You can never bridge the gap between the demand and supply of data science jobs. In fact, the talent gap is so large that an organization can never meet its 100% business demands within time and budget constraints.
However, there’s an alternate approach that can help reduce the gap to a wide extent — don’t get stuck chasing only the traditional eye-candy job roles in data science such as data scientists, data engineers, or data architects. It will only limit your ability to form a diverse team. Instead, analyze what you really need and choose the best-suited roles for your team and organization. Designers and storytellers are roles in data science teams too.
Check out 5 job roles that would build a perfect data science team for you
The demand for data science talent in the U.S.A
Here’s an analysis we did on the job posting data on LinkedIn in the U.S. for December 2019. We only chose job postings with relevant keywords such as data or data science.
1. Highest data science job demand by job type
The total number of jobs posted on LinkedIn with relevant keywords were 55,469. Out of which, 50,722 jobs were for full-time positions, where organizations look for long-term commitment and engagement. Unfortunately, the demand for internships, part-time, and contractual data science positions is significantly lower.
2. Highest data science job demand by location
Next, we sorted the job postings by location. We were sure that Silicon Valley, San Francisco, would emerge as the hub of Data Science jobs. But surprisingly, it was Seattle, Washington with the highest demand of 3,668 Data Science jobs, followed by New York with 3,394 jobs.
3. Highest data science job demand by Experience/Skill level
The analysis also revealed that unlike other jobs, the demand for entry-level positions for data science is much higher. However, organizations highly demand talent with associate-level experience. 17,528 job postings were rolled out for the associate level experience, followed by 13,640 job postings for entry-level candidates. This clearly indicates that organizations are trying to build their data science teams from ground level, ensuring a perfect mix of senior and junior level employees.
4. Highest data science job demand by Industry
It is also important to understand the industry and verticals that are keen to do more with data. Another insight from the analysis indicated that the computer software industry rolled out most of the jobs (22,469), followed by the internet, financial services, pharma, and healthcare.
Where’s the talent to meet the demand?
Post the analysis, we found a report from Hacker Rank (July 2019) that clearly illustrated where data science talent is present. Over 30% of the talent is in the USA. India comes next with over 23% of the available talent pool.
Another survey from Kaggle offers a clear indicator that most of the data science experts are a part of large enterprises that have more than 10,000 employees. This means that the majority of the talent is already at the disposal of tech giants. However, startups are not far behind in the race to hire talent to solve complex business problems with data science.
A data science team is a blend of diverse roles
Too many firms chasing the limited pool of established Data Science talent is one of the reasons that there is a huge gap between the demand and supply of talent. The diversifying skillset in the field of data is giving rise to emerging roles in data science such as data storytellers, data ethicists, and behavioral psychologists. Organizations need to understand that a data science team needs more than just data scientists. There are various stages in data science projects that people with specific skills can handle delicately. Moreover, the combination of diverse experience and roles can offer better ROI for the projects.
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