Why Are Data Scientists In Demand?

The big data market is currently seeing large-scale acceleration as businesses look to leverage their data. Regardless of industry or business size, companies across the spectrum are using data to drive business decisions, streamline operations, and strategically position themselves for future growth.

In conversations with our clients, we are seeing a record level of interest in hiring data professionals. Why? Many businesses have communicated that building out their data teams, including key data scientist hires, is a priority for them this year.

In recognition of this increasing data scientist demand, this article aims to answer what data scientists do, why their skillsets are on the IT roadmap for many businesses and what data scientists should be aware of to continue to thrive beyond 2025.

What do data scientists actually do?

Before exploring why are data scientists in demand, it is important to first understand what the job role involves, as well as the impact data scientists have within businesses.

Data scientists are analysts who specialise in transforming raw data within organisations into actionable insights, which are then communicated to key stakeholders, who can use them to inform business decisions. These insights are invaluable and help to provide evidence on a variety of topics from customer buying patterns to inefficiencies within departments, and more.

Data scientists in their day-to-day responsibilities will extract, analyse and interpret large amounts of data produced by their organisation and transform it into information that stakeholders and other parties of interest can digest. In addition to data analysis tasks, data scientists often source new data, build machine learning models, or AI systems, and help integrate these tools into their company’s or client’s processes with the aim of improving operational efficiency.

Why are data scientists in demand?

Big data is an ever-expanding industry, with data scientist roles expected to grow by 36% between 2023 to 2033. As companies turn towards greater digitalisation and collecting increasing amounts of complex data, they are also exploring how to leverage it effectively. Thus, data scientists and other job roles within data science (such as data analysts, data architects and data engineers) have risen sharply in demand.

Shifting business strategies

In conversations with our clients, we have found that many businesses are moving away from traditional rigid data-reporting ETL processes with on-premise environments to store data, to more cloud-based data technologies instead. By migrating their data to online cloud-based platforms, they can significantly increase their data storage and make use of the AI capabilities built into the platform. This, in turn, has led to many businesses building out their data teams to make full use of this greater digitalisation.

Managing large amounts of data

It is estimated that 90% of the world’s data has been generated in the past 2 years alone. Furthermore, the size of big data available will rise by 33% year-on-year between 2023 and 2030. With 64% of businesses managing one petabyte of data (which is equivalent to 20 million tall filling cabinets worth of data) and 41% of businesses managing approximately 500 petabytes of data, many companies are drowning in unstructured raw data.

Businesses who secure data scientist talent for their teams will be able to effectively manage this data and maximise the beneficial outcomes possible from data collection.

Increasing profits

On the whole, businesses who do not have a dedicated data scientist, or other data professional, are not fully utilising the data they possess. Data-driven decision-making can significantly increase a company’s profitability and productivity, with statistics showing it can cause an average 8-10% rise in profits. This increase in profits can be attributed to the valuable insights that data scientists offer that improve efficiencies and drive innovation, allowing businesses to gain an advantage over their competitors.

Building AI models

Predictive AI models run on the analysis of large sets of data. As businesses look to fully invest and utilise AI, data scientists are in demand to help build these predictive AI models and use them effectively within their roles. Whilst some may question whether AI will eventually take over data-related job roles, this looks unlikely, with many data scientists using AI within their processes to reduce repetitive tasks and complement their skills and value-adding deliverables to their businesses.

Data science forecasting for 2025 and beyond

Overall, the market for data scientists is growing in demand and we only predict this trend to continue throughout this year and beyond. Some of our key predictions that will affect data scientists are set out below.

Greater AI integration

As the number of UK businesses who have fully adopted AI into their operations is set to climb to 22.7% this year, data scientists will see their opportunities continue to rise, as companies look to hire data scientists to support their AI initiatives. In turn, this will mean that data scientists will need to expand their skills within AI to include deep learning, machine learning, and natural language processing, in order to maximise their chances of easily securing work.

Focus on ethics

A growing debate within AI that data scientists will need to keep in mind when building AI tools or platforms is how they source data and how the platform is trained. For many, a core concern with AI is the bias that can be present within the platform’s training materials, which can affect the responses the machine provides end users. Data scientists will need to be aware of this and, with best practice, ensure systems are transparent, fair, and responsible in the datasets they choose to use and how they train the models.

Increase need for interdisciplinary skills

With more data scientists using automation to streamline repetitive tasks, such as data cleaning, there is a growing availability for data scientists to focus on more higher-level strategic work. With their time freed up from simple but time-consuming tasks, many will find they have more time to work on additional value-adding services for their clients/ employers. This will mean that skills within data visualisation, stakeholder management and sector-specific business acumen should be further developed in order for data scientists to command higher salaries.

Overall, as we continue through 2025, data scientists will be high in demand amongst businesses, with the number expected to rise in the future. The skills and responsibilities of a data scientist may change in line with increasing AI and automation adoption, however, many will find that this enhances their services rather than decreases their demand.

VIQU IT is an award-winning IT recruitment agency; if you are looking for excellent data scientist talent, our team are well-positioned to secure the best in class for your team. For more information on how we can support you, get in touch with us here.