The headlines surrounding tech layoffs have been stark: since the start of the year, 421 tech companies have laid off 119,593 staff globally.
In the UK, high rates of venture capital funding that fuelled hiring growth during the pandemic have slowed significantly, dropping by 22% in 2022. In turn, this has had a knock-on impact across hiring in many sectors, including the neobanking sector.
So what does this mean for tech workers in the UK? While no sector is immune to redundancy, certain jobs are proving more resilient than others. And along with roles rooted in AI, AR/VR and cloud software solutions, data scientists continue to be in demand as organisations bolster their productivity, agility and overall performance via data-driven results.
Why is data science so important?
The days of going with your gut feeling or a hunch are long gone. Data is what drives businesses today and this requires data scientists to conduct analysis and propose actionable insights based on this information.
According to recent findings, data science is one of the fastest-growing and in-demand job titles in the UK. Machine learning in particular has become an increasingly important element of the job as companies lean on vast amounts of AI-generated data to streamline decision-making processes in real-time.
Predictive analytics are also being used to defend companies against cyberattacks, something 39% of UK businesses experienced in 2022.
There are also employment opportunities outside of tech: from the retail sector to cancer research, the scope for employment is wide and varied, meaning data scientists can align themselves to an industry or profession they’re passionate about, or deliver a product they have a personal interest in.
Is it possible to pivot to data science?
Typically data scientists have a bachelor’s degree in computer science or a related field, or a master’s degree in data science, so it is possible for new graduates or those who return to education to pivot to a career in data science. Many data scientists also participate in tech bootcamps or complete professional certificates throughout their careers to keep on top of the latest developments in the field.
You’ll also need experience with a programming language—Python and SQL are two of the most popular and widely used globally by organisations that employ data scientists.
The UK government is also helping those who work in the public sector realise their potential in the field of data science. In 2022 the Data Science Partnership was formed to offer the Data Science Accelerator programme for aspiring data scientists as well as a Data Visualisation Accelerator programme.
Ready to take the next steps to secure a data science role? The UKTN Job Board has hundreds of roles in companies that are actively hiring, like the three below.
Senior data scientist, Lendable, London
Lendable is hiring a senior data scientist to help it achieve its mission to make consumer finance cheaper and faster. One of the UK’s newest unicorns, it has focused its efforts on loans, credit cards and car finance and its employees work in small teams to solve problems and find smarter solutions.
In this role, you’ll work to develop the credit risk models to underwrite loan and credit card products. You’ll also be tasked with identifying issues, translating business problems into data questions and proposing solutions. You’ll also extract, parse and transform data for use in machine learning, analytic evaluation and investment reports. Applicants should have experience using Python, Juniper, Pandas and Numpy, and knowledge of machine learning techniques. See more details here.
Data scientist, Third Republic, London
Third Republic is seeking a data scientist to help build statistical models to solve specific operational problems such as predicting equipment failure. In this role, you’ll be required to mentor team colleagues, collaborate with talented data scientists from leading client organisations, work through clients’ entire data ecosystems to understand their requirements and optimise performance needs by gathering meaningful insights.
The ideal candidate will have an advanced degree in a quantitative discipline such as statistics, mathematics, econometrics or economics, five-plus years of experience in predictive analytics and machine learning, expertise in R, Python, Julia, SQL, GMPL and a deep understanding of TensorFlow. View the full job description.
Staff data scientist, Intercom, London
Intercom’s research, analytics and data science (RAD) team uses data to drive product strategy, and shape products that deliver efficient and personal customer experiences. As a staff data scientist you’ll build and automate actionable models and dashboards and craft data stories to advocate for your recommendations across the company. You’ll also be required to design, build and update end-to-end data pipelines, working closely with stakeholders to drive the collection of new data and the refinement of existing data sources and tables.
You should have seven-plus years of experience working with data to solve problems and drive evidence-based decisions, excellent SQL skills, strong proficiency with a coding language like R or Python and experience working on a B2B Says product. If you get really excited about asking the right questions, exploring patterns in data and surfacing actionable insights, then this role is for you. Apply now.