From layoffs to widespread concerns about the impact AI will have on jobs, the first half of 2023 has been tumultuous for tech work workers across the globe. In April, the term “will AI take my job” registered a search interest of 100 on Google, up from 21 in July 2022.
But is there any truth to the rumours or concrete evidence that proves AI is a cause for concern when it comes to jobs?
On one side of the coin, data from Goldman Sachs predicts that generative AI tools could impact as many as 300 million full-time jobs worldwide.
Similarly, evidence compiled by Accenture estimates that 40% of all working hours could be affected by generative AI.
Conversely, the World Economic Forum (WEF) predicts that by 2025, 97 million new jobs will have been created thanks to AI.
And in its 2023 Future of Jobs report, the WEF cites big data analytics, climate change and environmental management technologies, along with encryption and cybersecurity, as the primary drivers of career advancement over the next five years.
Data science job evolution
When you look at where data science is now — and how far it has come in recent years — it’s not surprising that the field will continue to thrive as an increasing number of companies adopt digitisation and the cloud.
According to McKinsey, 32% of companies are adapting their longer-term strategies to reflect and respond to changes brought about by data and analytics.
The UK government has also been actively working to support growth in the sector and the UK Government Data Science Partnership, which was created to help the government realise the potential of data science, offers a Data Science Accelerator programme for aspiring data scientists as well as a Data Visualisation Accelerator programme.
Cloud computing has also changed the way data is being processed and analysts now have access to vast sets of information — often millions or billions of inputs — that cannot be interpreted manually.
For those already working in the field, up-skilling and continuous learning are also crucial as statistics and modelling are fast being replaced by coding and prompt engineering so proficiency in machine learning is necessary to ensure the correct insights are being gained.
As such, data scientists with the necessary skills and experience are in high demand as companies vie for top talent.
Below are three that are hiring and as ever you can find many more opportunities in data science, data analytics and data engineering on the UKTN Job Board.
Data engineer, BT Group, London
As a data engineer at BT Group you will work in the capture, management, storage and utilisation of structured and unstructured data from internal and external sources, turning business needs into the data that supports the BT Group’s data strategies and strategic decision making.
Day-to-day you will deliver the coding, testing and deployment of data processes, contribute towards the architecture and design patterns to process and store high-volume data sets and support the implementation of ways to improve working processes within the area of data engineering responsibility through data analysis.
Data scientist, Marshmallow, London
Insurtech startup Marshmallow is seeking a data scientist to generate actionable insights beyond pricing and fraud and help the business move into other areas including claims.
In this role, you will uncover and drive forward new high-impact opportunities, work within a cross-functional team of engineers, designers, analysts and product managers, influence the team’s roadmap using data to quantify new opportunities and be a champion on data so that you can solidify data-driven processes within the team.
Data engineer, Global Radio Services, London
Reporting to the head of data, and focused initially on DAX, a digital advertising exchange which connects brands with audiences at scale across connected audio and digital out-of-home, the data engineer will be responsible for building and evolving key DAX data services such as publisher and advertiser insights, identity resolution and audience modelling.
The new hire will also play a central role in crafting and defining data architecture, get training and hands-on experience on the latest tools and technologies such as AWS, Apache Spark and K8s, and contribute to the development of streaming data pipelines.