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Featured Jobs

Strategy Intern (Capital Markets) - 3 months

About the CompanyCruxy & Company is a leading tech-enabled growth specialist firm specialising in innovative and data-driven solution for the B2B technology and software space. We pride ourselves on our dynamic team, product/market specialism and cutting-edge analytical methodologies to solve complex growth challenges. Our mission is to empower clients with actionable insights and robust growth strategies.The RoleThis is not an...

Cruxy
London

Commercial Lead Surveyor

Their group have grown since then to offer a full spectrum of property services including: Planned and Project works in Painting, Roofing, Flooring, Passive and Active Fire Protection, Kitchen and Bathroom Replacements, Multi-Disciplinary Fabric Upgrades, Retrofit and Energy Services and Response and Void Maintenance Contracts, delivered by expert, directly employed teams across 40 branches.Their largest sectors are Social Housing, Defence,...

Camden Town

Senior Software Engineer

Senior Software Engineer - JavaScript / AWSMy client is undergoing an exciting digital transformation, re-platforming its technology stack. They are seeking a Senior Software Engineer to play a key role in shaping the future of their digital platforms. You will lead the design, execution, and integration of cutting-edge solutions across eCommerce, Order Management, and Business Intelligence, working closely with internal...

Manchester

Commercial Analyst

Job Description SummaryResponsible for delivering analysis to support B2C Breakdown Retention performance optimisation, producing reports and models to aid informed decision making and enhance customer outcomes. You'll be developing your technical skills while providing regular and ad-hoc analysis to support commercial retention marketing as well as the inbound and outbound retention contact centre teams.ResponsibilitiesProduce regular and ad-hoc analysis to understand...

Basingstoke

Oracle PL/SQL Developer

Oracle PL/SQL Developer – Database Applications - Stoke, Stoke on Trent, StaffordshireMid-level Oracle Developer role - 40-50k will suit someone with 2-3 years plus development exp.We are looking for a talented Oracle PL/SQL Developer to join this development team and play a key role in designing, developing, and maintaining database applications. This is an opportunity to work in a stable,...

Stoke-on-Trent

SENIOR DATA SCIENTIST - Computer Vision / Generative AI HYBRID

Senior Data Scientist - Computer Vision / AI Data Scientist / Generative AIHYBRID / BRISTOL 3 days per weekUnlock the Power of AI Innovation!Join my client, an AI trailblazer with an international presence, helping industries like healthcare, sports, manufacturing, and agriculture transform through advanced artificial intelligence solutions. As a Data Scientist specialising in Computer Vision, you'll play a pivotal role...

Bristol
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Industry Insights

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Careers

Navigating Data Science Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Data science has taken centre stage in the modern workplace. Organisations rely on data-driven insights to shape everything from product innovation and customer experience to operational efficiency and strategic planning. As a result, there is a growing need for skilled data scientists who can analyse large volumes of data, build predictive models, communicate findings effectively, and collaborate cross-functionally. If you are looking to accelerate your data science career—or even land your first role—attending data science career fairs can be a game-changer. Unlike traditional online applications, face-to-face interactions let you showcase your personality, passion, and communication skills in addition to your technical expertise. However, to stand out in a busy environment, you need a clear strategy: from polishing your personal pitch and asking thoughtful questions to following up with a memorable message. In this article, we’ll guide you through every step of making a strong impression at data science career fairs in the UK and beyond.

Jobs

Common Pitfalls Data Science Job Seekers Face and How to Avoid Them

Data science has become a linchpin for decision-making and innovation across countless industries, from finance and healthcare to tech and retail. The demand for data scientists in the UK continues to climb, with businesses seeking professionals who can interpret complex datasets, build predictive models, and communicate actionable insights. Despite this high demand, the job market can be extremely competitive—and many applicants unknowingly fall into avoidable traps. Whether you’re an aspiring data scientist fresh out of university, a professional transitioning from a quantitative role, or a seasoned analyst looking to expand your skill set, it’s crucial to navigate your job search effectively. In this article, we explore the most common pitfalls data science job seekers face and provide pragmatic advice to help you stand out. By refining your CV, portfolio, interview strategies, and communication skills, you can significantly increase your chances of landing a rewarding data science role. If you’re looking for your next data science job in the UK, don’t forget to explore the listings at Data Science Jobs. Read on to discover how to avoid critical mistakes and position yourself for success.

Careers

Career Paths in Data Science: From Entry-Level Analysis to Leadership and Beyond

Data is the lifeblood of modern business, and Data Scientists are the experts who turn raw information into strategic insights. From building recommendation engines to predicting market trends, the impact of data science extends across virtually every industry—finance, healthcare, retail, manufacturing, and beyond. In the UK, data-driven decision-making is critical to remaining competitive in a global market, making data science one of the most sought-after career paths. But how does one launch a career in data science, and how can professionals progress from entry-level analysts to senior leadership roles? In this comprehensive guide, we’ll explore the typical career trajectory, from junior data scientist to chief data officer, discussing the key skills, qualifications, and strategic moves you need to succeed. Whether you’re a recent graduate, transitioning from another technical field, or an experienced data scientist aiming for management, you’ll find actionable insights on forging a successful career in the UK data science sector.

Jobs

Job-Hunting During Economic Uncertainty: Data Science Edition

Data science has become essential for modern businesses, enabling data-driven decisions that enhance efficiency, profitability, and strategic foresight. From predictive analytics in finance to recommendation engines in retail, data scientists sit at the crossroads of statistics, programming, and domain expertise, building models that translate raw information into tangible insights. Yet, when broader economic forces create uncertainty—through market downturns, shifting investor priorities, or internal budget constraints—data science roles can experience increased scrutiny, competition, and extended hiring cycles. Despite these pressures, data-driven approaches remain crucial to organizations looking to weather challenges and find opportunities in volatile environments. Whether you’re refining advanced machine learning techniques, fine-tuning data pipelines, or collaborating with business stakeholders on dashboards, your skill set is often still in demand. The key is adapting your job search strategy and personal branding to cut through the noise when fewer roles may be available. This article explores: Why economic headwinds affect data science hiring. Actionable strategies to stand out in a tighter job market. Ways to emphasize your technical and soft skills effectively. Techniques to maintain focus and resilience despite potential setbacks. How www.datascience-jobs.co.uk can help you secure the ideal data science position. By combining strategic thinking, polished communications, and adaptability, you can land a fulfilling data science role that leverages your expertise—even if the market feels more demanding.

Careers

How to Achieve Work-Life Balance in Data Science Jobs: Realistic Strategies and Mental Health Tips

Data science has quickly emerged as one of the most influential fields in the modern workplace, shaping how businesses make critical decisions and expanding our understanding of everything from consumer behaviour to public health trends. As the global demand for data insights continues to rise, companies of all sizes are seeking professionals who can effectively harness analytics and machine learning to drive innovation. Yet, this promise of limitless opportunity comes with significant challenges. Data scientists often grapple with large volumes of complex data, tight project deadlines, cross-functional collaboration, and constant upskilling. Amid the excitement of discovering actionable insights and developing high-performing models, many wonder if it’s truly possible to maintain a healthy work-life balance. With the field evolving at breakneck speed, the intensity of these roles can leave even the most passionate data professionals drained and questioning how to protect their personal well-being. This article delves into the reality of high-intensity data science jobs, offering practical guidance on setting realistic expectations and preserving mental health. We’ll look at common pitfalls like burnout and perpetual “always learning” pressure, while also highlighting proven strategies for boundary-setting and effective time management. Whether you’re a seasoned data architect, an aspiring machine learning engineer, or somewhere in between, you’ll find actionable tips to help you manage your career trajectory without sacrificing your personal life.

Careers

From Research Labs to Real-World Insights: How Academic Researchers Can Thrive in Data Science

Over the past decade, the data science revolution has swept across industries—retailers predicting shopping habits, hospitals personalising patient treatments, and finance companies detecting fraud in near-real time. This surge in data-driven decision-making has created a pressing need for specialists capable of extracting meaningful insights from complex datasets. As a result, PhD holders and academic researchers are uniquely positioned to bring high-calibre analytical skills to the commercial realm. But transitioning from academia to data science can seem daunting: Where do you begin? How do you communicate your research background in industry-friendly terms? What new tools should you learn? This comprehensive guide, explores the paths, challenges, and strategies for academics making the leap into data science. You’ll discover how to leverage your scholarly expertise, adopt a commercial mindset, and build a career that transforms raw data into actionable insights—fostering innovations across every sector of the economy.

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