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When 64% of employees in data science, AI and machine learning attended training or obtained new certifications in the previous year, the average change in return was $ 9,252 – an increase of 2.25% annually. That’s one of the findings in O’Reilly’s 2021 Data / AI Salary Survey, which looked at job satisfaction and pay in the data science sectors experiencing a shortage of qualified employees. The results suggest that data and AI professionals are among the most active employees when it comes to upskilling – and have a clear desire to learn.

“Given the shortage of qualified personnel in areas such as science, machine learning and AI, companies that are serious about increasing their workforce should invest in education and training to develop this talent internally,” said Laura Baldwin, president of O’Reilly. The statement said “With the talent of the hungry talent and the recovering global economy to fill the tech role in the digital work environment, there has never been a better time to invest in employee education and recycling.”

The lament over the lack of AI talent in the U.S. has become a familiar barrier to private industry. There are about 300,000 AI professionals worldwide but “millions” of roles are available, according to a report by Chinese tech company Tencent. In 2018, Element AIA estimated that of the 22,000 PhD-educated researchers working on AI development and research globally, only 25% are “so well versed in technology that they can move from research to application with teams.” And a 2019 Gartner survey found that 54% of chief information officers consider this skill gap to be the biggest challenge facing their organization.

Data Science Upskilling

The O’Reilly survey polled 3,136 employees and compiled salary data based on gender, level of education, job title and equipment and platform skills. Ninety-one percent of those earning an average of 14 146,000 per year showed interest in learning a new skill or improving an existing one, and those who took the time to learn were rewarded with a large salary increase. According to O’Reilly, employees who participated in one to 19 hours of training saw an average salary increase of only 7 7,100, while those who devoted more than 100 hours saw an average bump of $ 11,000 in annual pay.

Indeed, data scientists responding to the survey believe that acquiring new technological skills will give them more job responsibilities, increased hiring capacity, and more job security. This is generally true, but payroll difficulties in data science – like the broader tech industry – depend in part on gender, O’Reilly found. Women’s salaries are significantly lower than men’s, which is 84% ​​of the average salary for men, regardless of education or job title. For example, at the executive level, the average salary for women was $ 163,000 versus $ 205,000 for men, O’Reilly found – 20% difference.

Previous studies have identified inequalities in data science recruitment with gender and ethnic lines. For example, despite 70% entry-level data and analytics roles, minority-ethnic groups account for less than half of technical leads and directors. The BCG survey found that the region’s “male-dominated competitive culture” topped the list of information science concerns of many female college students; It is estimated that about 15% of data scientists today are women.

Twenty-two percent of those reported to O’Reil say they are considering changing jobs due to a lack of salary increases over the past year. Meanwhile, 18% said their salaries have remained the same over the past three years.

Recruitment boom

In a June 2020 report, LinkedIn found that the epidemic had reduced the demand for AI talent from employers as well as the enthusiasm of job applicants. During the 10 weeks immediately following mid-March, the growth rate slowed, with the list for AI roles falling to just 4.6% year-over-year from 14% before the outbreak.

The Data Science and Analytics team plans to hire an 81% data science and analytics team in Q3 or Q4 of 2021, and the U.S. Bureau of Labor Statistics predicts that the number of data science jobs will increase by 28% by 2026. But the salary is heavy. Depending on the programming tools selected by the job applicants. According to O’Reilly, professionals who use rust have the highest average salaries (over $ 180,000), followed by Go ($ 179,000), Scala ($ 178,000) and Python ($ 150,000). Expertise in PyTorch (166,000), TensorFlow ($ 164,000), and scikit-learn (157,000) was paid at best, while the highest salaries were H2O (183,000), KNIME ($ 180,000), Spark NLP (179,000), And Spark were associated with MLlib. ($ 175,000).

“Our survey shows how data and AI professionals are dedicated to advancing their careers through skills development and training. It is crucial for companies to acquire L&D rights to retain and attract top talent in this hot job market, ”said Mike Laukides, VP of report author and content at O’Reilly.


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