Our client are a medium sized defence consultancy looking for a Data Scientist to join their team. You’ll be joining a small, highly skilled technical team working on a live AI computer vision capability within a secure defence environment. The team focuses on sustaining and enhancing a production system, delivering incremental improvements and new use cases rather than experimental or...
Datasource
London
Data Scientist (Predictive Modelling) – NHS
Data Scientist (Predictive Modelling) – NHS SR2 Consulting has an urgent requirement for a Data Scientist to support an NHS client on a contract basis. Our client is delivering a data-led solution to support discharge planning and patient flow in an acute healthcare setting. We are seeking a data scientist with experience in predictive modelling, clinical data, and EPR systems...
SR2
Farringdon, Greater London
Data Scientist - Measurement Specialist
Our client,an award winning SaaS organisation providing software solutions to the SME marketplace, is now seeking an experienced Data Scientist for a 12 month contract. You will be assisting in the company transition from correlation-based reporting to causal-based decision making, helping guide key marketing investment decisions. Central London location, hybrid, with 3 days a week in the office. Responsibilities Forecasting:...
EF Recruitment
Victoria, Greater London
Data Scientist KTP Associate
Opportunity Overview This post is a dynamic role that will develop bespoke AI-driven tools to automate motor insurance claim analysis, enhancing efficiency and accuracy. The KTP will embed advanced machine learning capabilities, reduce case turnaround times, and unlock scalable growth, transforming data handling in the UK's high-volume, fraud-prone motor insurance sector. The position will be based at the company premises...
University of Salford
Salford
Data Scientist
Data Scientist £34,000 - £38,000 + benefits Full Time/Permanent Tamworth The Company Akkodis are partnering with a market leading manufacturing company who are looking for a driven Data Scientist to join their IT development team. This is primarily an office based role based at the head office in Tamworth, West Midlands. The Role The Data Scientist will drive the development...
Akkodis
Tamworth
Data Scientist- Fintech
DATA SCIENTIST- FINTECH LONDON UP TO £65,000 Join a fast-growing, data-driven FinTech expanding rapidly in the US- they operate across personal loans, credit cards, and auto finance, and are widely regarded as a leader in digital lending. THE ROLE You'll join a compact US-focused Data Science team, taking full ownership of the end-to-end model lifecycle. This isn't a traditional "build...
If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going.
With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up.
Here’s the straight-talk version most hiring managers won’t explicitly tell you:
👉 You don’t need to know every data science tool to get hired.
👉 You need to know the right ones — deeply — and know how to use them to solve real problems.
Tools matter, but only in service of outcomes.
So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood.
This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.
If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first.
Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.
Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models.
Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways.
And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem:
Many data science candidates are not job-ready.
Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired.
The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles.
This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.
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