Data Scientist

Tenth Revolution Group
Newcastle upon Tyne
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist - Gen AI - Remote

Data Scientist - Gen AI - Remote

Data Scientist - Gen AI - Remote

Data Scientist - Gen AI - Remote

A growing business in the retail / e-commerce space are looking for a Data Scientist to spearhead the use of Data Science techniques across the business, helping to drive improved business outcomes. This role is home-based, with travel to their office near Newcastle upon Tyne once per month to socialise with your team (expenses-paid).This is a new role, where you will be the company's sole Data Scientist as part of a small and growing data team, reporting directly into the Head of Data and AI.The core of the role will be developing and deploying Machine Learning models, which will be integrated into various platforms including their website, to allow for better customer personalisation and product recommendations etc.You will also implement ML Ops, will leverage AI tools such as Copilot to improve efficiency, and will work closely with the Data Engineers to ensure the successful integration and scaling of your solutions within their data infrastructure.They work on an AWS tech stack, but are open to seeing candidates from Azure backgrounds too, as long as you have experience leveraging Databricks as this is a core part of their tech stack.This is a brilliant opportunity for a Data Scientist to make a tangible impact to a business who are really investing in their data capabilities!Requirements Experience developing and deploying machine learning modelsSkills in Python, SQL and ML frameworks such as TensorFlow, PyTorch or scikit-learnHands-on experience with Databricks (either on AWS or Azure)Understanding of ML Ops principles is beneficialConfident working independently and a can-do attitude BenefitsSalary up to £60,000 depending on experience22 days annual leave plus bank holidays (rising to 25 days over time)Enhanced Maternity and Paternity leave policy Please Note: This is a permanent role for UK residents only. This role does not offer Sponsorship. You must have the right to work in the UK with no restrictions. Some of our roles may be subject to successful background checks including a DBS and Credit Check.Tenth Revolution Group / Nigel Frank are the go-to recruiter for Power BI and Azure Data Platform roles in the UK, offering more opportunities across the country than any other. We're the proud sponsor and supporter of SQLBits, and the London Power BI User Group. To find out more and speak confidentially about your job search or hiring needs, please contact me directly at

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

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 it’s 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, we’ll 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, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re 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 Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded 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, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s 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 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.