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Remote Permanent

AI Specialist

The AI/ML Specialist role at Snowflake involves driving sales and innovation by aligning technical solutions with customer needs. Key responsibilities include providing technical guidance, influencing the design of complex AI/ML solutions, and fostering collaboration across teams. The role demands a thought leader who can effectively communicate technical concepts and stay updated on industry advancements.

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Snowflake

Remote, United Kingdom

Remote Permanent Flexible Clearance Required

Lead Computer Vision Engineer

This role involves leading the development and deployment of cutting-edge computer vision solutions for high-stakes defence projects. You will act as a technical authority, architecting sophisticated systems, guiding multidisciplinary teams, and contributing to business development. The position offers significant autonomy and the opportunity to shape the technical strategy and mentor team members.

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Faculty AI

London, United Kingdom

On-site Contract Part-time

Research Assistant - Human Influence

The role involves designing and running studies to understand how frontier AI systems influence human attitudes and behavior, focusing on risks to human agency and wellbeing. You will work with top technical talent, run large-scale RCTs, and have the opportunity to lead-author or co-author publications.

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AI Security Institute

London, United Kingdom

Hybrid Permanent

Product Manager, Analytics

This role involves owning the end-to-end analytics product for enterprise learning and development, focusing on individual learner progress, programme-level reporting, and leadership views. You will work closely with customers, the engineering team, and designers to define and build a product that provides actionable insights and trusted data for learning leaders and executives.

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Synthesia

London, United Kingdom

Hybrid Permanent

EMEA Energy Industry Go-To-Market (GTM) Leader

This role involves leading the go-to-market strategy for Databricks in the energy sector across EMEA. Key responsibilities include setting the AI vision with top energy accounts, driving pipeline growth, and building cross-functional alignment with sales, engineering, and marketing teams. The position requires deep industry expertise and a proven track record in strategic consulting and technology commercialization.

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Databricks

United Kingdom

£700 – £750 pd Hybrid Contract Clearance Required

Data Architect

The Data Architect will lead the strategic integration of agentic AI and large language models across the enterprise, defining governance frameworks, advising senior stakeholders, and mentoring other architects. This role involves close collaboration with external AI providers and internal teams to ensure responsible AI practices and successful adoption.

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Experis

Croydon, London, United Kingdom

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Where to Advertise Data Science Jobs in the UK (2026 Guide)

Where to advertise data science jobs UK in 2026: the specialist boards, communities and channels that actually reach senior and lead data science talent. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

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Data Science Jobs UK 2026: What to Expect Over the Next 3 Years

Data Science Jobs UK 2026: roles, salaries and the trends shaping UK data science hiring over the next three years — from MLE crossover to GenAI workflows. Data science has spent the past decade being described as the sexiest job of the twenty-first century. By 2026, the reality is both more nuanced and more interesting than that label ever suggested. The discipline has matured, fragmented, deepened, and in some respects reinvented itself — and the jobs market has changed with it in ways that create genuine opportunity for those who understand what employers actually want, and genuine difficulty for those still operating on assumptions formed five years ago. The data science jobs market of 2026 is not simply a larger version of what it was three years ago. The generalist data scientist — equally comfortable wrangling data, building models, and presenting insights to the board — is giving way to a more specialised landscape where employers know exactly what problem they are trying to solve and are looking for candidates with the specific depth to solve it. Machine learning engineering, causal inference, experimentation, AI product development, and domain-specific applied science have all emerged as distinct career tracks within what was previously a single, loosely defined profession. At the same time, the arrival of large language models and the broader AI capability wave has both threatened and created data science roles in equal measure. Some of the work that junior data scientists spent their early careers doing — data cleaning, exploratory analysis, basic model building — is being partially automated by AI tooling. But the demand for practitioners who can evaluate AI systems rigorously, apply statistical thinking to complex business problems, and build the data foundations on which AI depends has grown considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what data scientists are expected to build and know, and how to position a data science career that will remain valuable as the field continues to evolve around them. This article breaks down what the UK data science jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.

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New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

New Data Science Employers to Watch in 2026: a UK and international shortlist of analytics and AI companies hiring data scientists, ML engineers and analysts. Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

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