Is Data Science & AI an Oversaturated skills market ? - Wyatt Partners (2024)

FAQs

Is data science going to be oversaturated? ›

Yes the field is oversaturated. But that doesn't mean it's not difficult to hire good Data Scientist's & Machine Learning Engineers. It's as hard as ever.

In conclusion, while some may argue that the market for data analysts is oversaturated, the evidence suggests otherwise. With the demand for data analysts continuing to grow and companies reaping the financial rewards of data analytics, it's clear that the future is bright for data analysts everywhere.

Looking towards the future of data analysis, artificial intelligence will play a more significant role. Data analysts won't go out of style because of this. Instead they will continue to develop their job and collaborate with AI to improve decision making and provide more insightful data.

We can also derive from the above that rather than being overhyped, data science is something that may soon become a necessity for growth and competitiveness, rather than a 'nice to have'. The only logical question at this stage would be: How viable is it moving forward? Extremely, as it turns out.

Long story short, we still need data scientists. Though, the role will probably change in the next future. It will focus more on the algorithms and the data science process, rather than on programming. At that, low code tools will make the implementation of the whole process even more approachable and faster.

“The AI market is not close to becoming saturated. Currently, companies have tried their hand here and there, with some proofs-of-concept materializing. The real large-scale production cases are only getting started, or are yet to come.”

Career advancement opportunities for Data Analysts in 2024 include moving into senior analyst roles, specializing in areas like machine learning or data science, transitioning into data engineering or business intelligence positions, or advancing into managerial roles overseeing data teams.

Data Science and AI

Most notably, the demand for natural language processing skills has increased from 5% in 2023 to 19% in 2024. Machine learning was mentioned in over 69% of data scientist job postings, with some ads specifying the required algorithms and methods.

The once seemingly invincible bubble of data science is rumored to be on the brink of bursting. This shift can largely be attributed to the maturation of the field. Data science is no longer an emerging discipline but a well-established field with specific demands and expectations.

Instead of posing a threat to data science jobs, it is much more likely AI will become extremely intelligent assistants to data scientists, allowing them to run more complex data simulations than ever before. Analytical skills will soon be required in many more traditional roles.

Will AI replace coders? ›

The short answer is no. The future of programming is not a battle between humans and AI; but rather more of a collaboration.

Professionals in both roles are highly compensated. However, AI engineers have higher salaries, on average, than data scientists. As of September 2022, the median annual salary for a data scientist was around $98,000, according to PayScale, with experienced data scientists earning $137,000 on average.

What Is the Risk of Data Science as a Career? Data science is undoubtedly a safe career to work in. However, it still imposes some risks in the future, leaving aspiring data scientists worried about whether or not to pursue it. The risk of pursuing data science as a career is the development of easy-to-use tools.

The sheer volume of data that needs to be analyzed can also be overwhelming, leading to high levels of stress. Additionally, the need to stay updated with constantly evolving technologies and tools adds to the pressure.

Data science careers require mathematical study because machine learning algorithms, and performing analyses and discovering insights from data require math.

As the pandemic subsided during 2022 & 2023, this saw a dramatic shift in the data science market: a hiring spree became a laying-off spree. Big tech companies cut down their job postings by 90%. It was a tough market for both the entry-level data scientist and the experienced scientist.

The field of data science research is expected to grow at a 22% rate from 2020 to 2030, says the US Bureau of Labor Statistics. This doesn't mean that machines would replace data scientists entirely, but it shows that AI and other automation tools can help them relieve the work with augmentation.

Data science will not become obsolete; instead, the field is predicted to grow in the near future.