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Flight Data AnalystOn site 5 days/Shift pattern£30,000 - £35,000 + OvertimeCapgemini are looking to recruit a Flight Data Analyst to join our team based in Brize Norton.Job PurposeSupport the A400M maintenance by capturing and transferring into MDS (Maintenance Data System) the maintenance information generated by the Part 145 during a mission. This covers the period prior to the aircraft departure...
Join one of the most prominant organisations within Insurance Broking as a Senior Business Analyst. In a role that focuses on a varied change portfolio within a large retails insurance division, you will support and introduce changes to business processes and systems delivering projects of different sizes and complexity including, but not limited to digital, regulatory, data transformation, system enhancements, ...
Big Data :Are you excited about taking your technical career to new heights with a full-time, W-2 role as a consultant in a dynamic and rapidly growing company? If you are, let's get in touch - your interest is the first step to starting the conversation.What This Role Requires:· 1-4 years of programming experience after your degreeMust have coding experience...
Our clients need technically strong UK-based back-end Python developers who are keen techies with a good level of knowledge for their experience: junior to mid-level developers who want to move up to the next level and get stuck into making a big difference in a small company.Every cycle, we review everything we do (including developers' work) with the intention of...
Legal Onboarding SpecialistA brilliant opportunity for a talented corporate law paralegal or contract law specialist, to work as a Legal Onboarding Specialist, joining a market-leading disruptive software technology firm in London. Offering excellent training, career progression and prospects, this is a unique opportunity to work for a rapidly expanding machine learning software house. This opportunity involves onboarding and implementing legal...
Job Title: Java Software Engineer (SC cleared)Location: hybrid - office locations Manchester or CroydonClearance required: Must hold active SC clearance.Contract length: 6 months +Seeking experienced Software Engineers with a deep understanding of Java (Spring Boot) and extensive experience working with large-scale microservice architectures. The ideal candidate is proficient in test-driven development (TDD) and has hands-on expertise in containerization (Docker) and...
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Data science has rapidly evolved into a driving force for businesses and organisations worldwide. In the United Kingdom, companies across sectors—including finance, retail, healthcare, tech start-ups, and government agencies—are turning to data-driven insights to boost competitiveness and innovation. Whether you specialise in statistical modelling, machine learning, or advanced analytics, data scientists are in high demand throughout the UK’s vibrant tech ecosystem. If you’re an international data scientist aiming to launch or grow your career in the UK, one essential part of the journey is navigating the country’s visa and work permit system. From understanding how to secure sponsorship as a Skilled Worker to exploring the Global Talent Visa for leading experts, this article will help you understand the most relevant routes, criteria, and practical steps for your move. Let’s delve into everything you need to know about working in data science in the UK as an international professional.
Data has become the linchpin of modern innovation. From forecasting consumer behaviour to enabling cutting-edge health research, data science underpins breakthroughs across nearly every industry. In the United Kingdom, the data science landscape is particularly robust, fuelled by a blend of academic excellence, government support, and vibrant private-sector collaborations. For jobseekers or career-changers keen to explore opportunities in this exciting field, DataScience-Jobs.co.uk offers a gateway to the latest openings, news, and resources. In this in-depth article, we’ll tour the top UK data science labs and institutes, highlight the unique research and career paths available, and outline how you can position yourself to thrive in a field that’s as dynamic as it is rewarding.
How to Find Mentors, Build Industry Connections, and Hone the Skills Needed in a Fast-Evolving Field Introduction Over the past decade, data science has grown from a niche academic discipline to a pivotal function driving decision-making in businesses of all sizes. With an array of applications—from predictive analytics and natural language processing to recommender systems and computer vision—data science offers an enticing career path for analytically minded professionals. However, as the field expands, so too does the level of competition. Employers seek not just theoretical knowledge but also real-world experience and robust problem-solving skills. That’s where shadowing and mentorship become game-changers for early-career data scientists. These hands-on learning opportunities provide an unmatched window into the workflows, tools, and soft skills you’ll need to excel in a professional environment. Whether you’re still completing your studies, fresh out of a bootcamp, or transitioning from another career, working closely with experienced data scientists can significantly shorten your learning curve and help you stand out when applying for your first full-time position. This article explores how to find mentors who align with your goals, the best ways to engage in shadowing opportunities, and practical tips for showcasing your growth as a mentee. From clarifying the nature of data science roles to leveraging online networks, you’ll discover how to position yourself as a candidate poised to solve complex challenges and drive data-driven innovation.
Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.
Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.
How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.
