The Demand for Data Science Jobs in 2022

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Data science remains one of today’s most dynamic industries, fueled by the enormous volumes of data generated by companies of every size and sector.

From product sales and material usage to employee work hours, the sheer variety of data offers rich opportunities for valuable insights that shape smarter strategic decisions.

Strong Growth Outlook for 2026

Data science enthusiasts enjoyed a strong year in 2019. The industry is set to perform even better in 2026, with global revenues projected to reach USD 274 billion (2019: USD 189 billion) and sustained annual growth of 13.1%.

The fourth industrial revolution continues to accelerate demand, creating millions of new data science roles in the years ahead.

The Demand for Data Science Jobs in 2026

This expansion is expected to deliver:

• Abundant opportunities for data scientists, data engineers, data analysts, analytics specialists, consultants, insights analysts, and related professionals
• Reduced costs, improved operational efficiency, access to new markets, and a clear competitive advantage

The prospects for the data science industry remain bright. Our world generates 2.5 quintillion bytes of data every day, a figure projected to reach 5.2 zettabytes by 2025—all requiring careful analysis.

Organizations that adopt a data-driven approach consistently outperform those that do not: data-driven insights have generated USD 1.8 trillion in profits, significantly lowered operational expenses, and boosted customer acquisition by a factor of 23.

By harnessing these insights, companies can make strategic, evidence-based decisions that keep them ahead of competitors and reshape traditional industry dynamics.

Key Big Data Trends in 2026

• Artificial intelligence (AI) and machine learning (ML) have given big data analysis a powerful boost.
• Acquisitions in the data sector now focus on core products rather than incremental feature additions.
• Only companies that deliver genuine innovation and measurable value attract funding.
• Automation frameworks have made it easier to develop practical big data use cases.

The rising number of data science positions underscores the growing need for specialized skills:

• According to the Royal Society, demand for professionals with data skills grew by 231% over the past five years.
• IBM estimates that approximately 28% of all jobs in 2026 will be data science roles.
• The US Bureau of Labor Statistics projects at least 19% growth in these positions by 2026.

Job Market Dynamics and the Talent Gap

The industry continues to hire at an exponential rate. Roughly 400,000 new positions opened between 2018 and 2019, particularly for administrators, analysts, architects, and engineers. During the same period, average salaries in big data and analytics rose by 28%.

Yet a significant skills shortage threatens to slow this momentum. IBM’s “The Quant Crunch” report highlights machine learning, big data, and data science as the most difficult skills to recruit for:

• The current rate of skill development among data science professionals is only 14%.
• A typical data science role remains unfilled for an average of 45 days.
• A 2019 KPMG survey of 3,000 technology leaders found that the “Data Analytics Expert” position was the hardest to fill.

LinkedIn data shows there are currently 2,186,308 big data professionals worldwide, while approximately 660,528 job postings were recorded in 2026. Demand for these skills is expected to keep rising, with information technology and services projected to account for 44% of new hires (2019: 36%). Financial services, recruitment, and software sectors will also absorb a meaningful share of talent.

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