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Role – Internal Account ManagerLocation – St AlbansSalary & Benefits– Very competitive negotiable salary, bonus structure; company pension; 25 days holiday, onsite parkingAlcedo Selection is proud to be partnering with the UK’s leading distributor of sheet plastic materials and roll media products. The company operates from 26 locations nationally and service a wide variety of different clients, working across many...
Role: Sales ExecutiveLocation: London / Office BasedPackage: £35k to £50k Basic plus Double OTE and BenefitsOur client is at the forefront of fibre connectivity in London, and they are now offering a wider range of internet and managed services to businesses across the capital.They are seeking a mid-market Sales Executive to drive new business and cross-sell and up sell to...
Entity:FinanceJob Family Group:Finance GroupJob Description:Derivatives Commodity Risk Senior Analyst (Product Control)Bp Trading and ShippingLocation – Canary Wharf (hybrid) 3 days office, home working 2 daysThe Derivatives Commodity Risk Team sits within Finance, Trading & Shipping, providing effective control and risk governance for crude and products options and derivatives trading globally.As a Senior Analyst you will be responsible for improving the...
Join us as a Model Risk ManagerIn this key role, you’ll undertake the validation of derivative pricing models and ensure that models are managed within the requirements of the bank’s model risk policy and risk appetiteYou’ll ensure model limitations are identified, communicated to stakeholders and effectively mitigatedWe’ll look to you to help develop, maintain and implement proportionate mandatory procedures for...
NEW SENIOR TEST ENGINEER BASED IN LITTLEHAMPTON.Our client based in West Sussex has a new quality engineer role, which is responsible for investigating and analysing the root cause of product failures. Working collaboratively with cross-functional engineering teams to identify root causes and implement corrective actions.Responsibilities as a Senior Test Engineer in Littlehampton.Conduct visual, electrical, mechanical, and other testing methods (both...
Entity:Customers & ProductsJob Family Group:Business Support GroupJob Description:Register your interest in future roles for Customer Care Team Leader - German speaking, for fixed term 6 months at our Milton Keynes site.Here at bp pulse, we're energising the future of transportation by developing fast and convenient charging solutions for consumer and commercial electric vehicles. Over the course of more than 10...
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Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.
Data science has emerged as one of the most influential fields in the 21st century, transforming how organisations make decisions, improve services, and solve complex problems. Nowhere is this impact more visible than in the UK public sector. From the Government Digital Service (GDS) to the National Health Service (NHS) and the Ministry of Defence (MOD), government departments and agencies handle vast amounts of data daily to support the well-being and security of citizens. For data enthusiasts looking to make a meaningful contribution, data science jobs in the public sector can offer rewarding roles that blend innovation, large-scale impact, and societal benefit. In this comprehensive guide, we’ll explore why data science is so pivotal to government, the roles you might find, the skills needed, salary expectations, and tips on how to succeed in a public sector data science career.
Data science sits at the intersection of statistics, machine learning, and domain expertise, driving crucial business decisions in almost every sector. As UK organisations leverage AI for predictive analytics, customer insights, and automation, data scientists have become some of the most in-demand professionals in the tech job market. By 2025, data scientists with expertise in deep learning, natural language processing (NLP), and MLOps are commanding top-tier compensation packages. However, deciding whether to become a day‑rate contractor, a fixed-term contract (FTC) employee, or a permanent member of an organisation can be challenging. Each path offers a unique blend of earning potential, career progression, and work–life balance. This guide will walk you through the UK data science job market in 2025, examine the differences between these three employment models, present sample take‑home pay scenarios, and offer strategic considerations to help you determine the best fit for your career.
Beyond Jupyter Notebooks Ask most people what a data‑science career looks like and they’ll picture Python wizards optimising XGBoost hyper‑parameters. The truth? Britain’s data‑driven firms need storytellers, strategists, ethicists and project leaders every bit as much as they need statisticians. The Open Data Institute’s UK Data Skills Gap 2024 places demand for non‑technical data talent at 42 % of all data‑science vacancies—roles focused on turning model outputs into business value and trustworthy decisions. This guide highlights the fastest‑growing non‑coding roles, the transferable skills many professionals already have, and a 90‑day action plan to land a data‑science job—no pandas required.
When CEOs need to unlock billion‑pound efficiencies or launch AI‑first products, they often call McKinsey & Company. What many graduates don’t realise is that behind every famous strategy deck sits a global network of data scientists, engineers and AI practitioners—unified under QuantumBlack, AI by McKinsey. From optimising Formula One pit stops to reducing NHS wait times, McKinsey’s analytics teams turn messy data into operational gold. With the launch of the McKinsey AI Studio in late 2024 and sustained demand for GenAI strategy, the firm is growing its UK analytics headcount faster than ever. The McKinsey careers portal lists 350+ open analytics roles worldwide, over 120 in the UK, spanning data science, machine‑learning engineering, data engineering, product management and AI consulting. Whether you love Python notebooks, Airflow DAGs, or white‑boarding an LLM governance roadmap for a FTSE 100 board, this guide details how to land a McKinsey data‑science job in 2025.
Data Science has evolved into one of the most popular and transformative professions of the 21st century. Yet as the demand for data-related roles expands, other fields—such as Data Mining and Business Intelligence (BI)—are also thriving. With so many data-centric career options available, it can be challenging to determine where your skills and interests best align. If you’re browsing Data Science jobs on www.datascience-jobs.co.uk, you’ve no doubt seen numerous listings that mention machine learning, analytics, or business intelligence. But how does Data Science really differ from Data Mining or Business Intelligence? And which path should you follow? This article demystifies these three interrelated yet distinct fields. We’ll define the core aims of Data Science, Data Mining, and Business Intelligence, highlight where their responsibilities overlap, explore salary ranges, and provide real-world examples of each role in action. By the end, you’ll have a clearer sense of which profession could be your ideal fit—and how to position yourself for success in this ever-evolving data landscape.
