Related Jobs
View all jobsBusiness Data Analyst
Data Analyst - Financial Crime
Group Director, Business Intelligence & Customer Master (BasĂŠ Ă London)
Data Engineer
Data Analyst - Data integrity
Get the latest insights and jobs direct. Sign up for our newsletter.
Industry Insights
Discover insightful articles, industry insights, expert tips, and curated resources.
Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)
Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether itâs building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, weâll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, youâll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when youâre ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.
Data Science Job Interview WarmâUp: 30 Real Coding & SystemâDesign Questions
Data science has become one of the most soughtâafter fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sectorâfinance, healthcare, retail, governmentârely on data scientists to build predictive models, understand patterns, and shape strategy with dataâdriven decisions. If youâre gearing up for a data science interview, expect a wellârounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, weâll explore 30 real coding & systemâdesign questions commonly posed in data science interviews. Youâll find challenges ranging from algorithmic coding and statistical puzzleâsolving to the architectural side of building data science platforms in realâworld settings. By practising with these questions, youâll gain the confidence and clarity needed to stand out among competitive candidates. And if youâre actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. Itâs a comprehensive hub featuring junior, midâlevel, and senior data science vacanciesâspanning startâups to FTSE 100 companies. Letâs dive into what you need to know.
Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained
Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industryâfrom finance and healthcare to retail, entertainment, and AI research. As a midâsenior data scientist, youâre not just running predictive models or generating dashboards; youâre 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 talentâespecially in the UK, where demand often outstrips supplyâroutinely 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 offerâfrom understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, youâll 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.