National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Scientist - Marketing Analytics & AI - West London

North Richmond
4 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist - AI / ML, Python, Scripting, Cyber Security

Data Scientist - Inside IR35 contract

Data Science Placement Programme

Data Science Placement Programme

Data Scientist - Marketing Analytics & AI

Location: West London or Leeds - Hybrid

I’ve partnered with a boutique Tech and Data Consultancy that works with some of the world’s-leading brands across retail, telecommunications, sports, and FMCG sectors to find a Data Scientist to join their team.

As the first Data Scientist on the Analytics team, you will be influential and work with autonomy from the start to build Machine Learning models for large client data sets. You will work on a variety of client projects and drive their Data Science approach.

Key Responsibilities

  • You will design and implement production-ready machine learning models for marketing attribution, customer behaviour analysis, and next-best action recommendations

  • You will provide expert consultation on advanced analytics, data engineering best practices and scalable data products that drive client decision-making

  • You will communicate complex technical findings to non-technical stakeholders

  • Champion AI adoption across client projects, identifying and implementing innovative solutions

    To be considered you will have proven experience in many of the following:

  • A proven track record in delivering data science projects focused on marketing, sales, and customer experience optimization

  • Expert knowledge of machine learning techniques including clustering, classification, and regression

  • Strong production-level coding skills in Python and SQL

  • Experience with major cloud platforms (AWS, Azure, or Google Cloud)

  • Proficiency with data warehousing technologies (Databricks, BigQuery, or Redshift)

  • Experience with data visualization tools (Tableau, Power BI, or similar)

  • Competent with Git for version control

  • Knowledge of digital behavioural data analytics (e.g., GA4 or Adobe Analytics) is advantageous

    Salary: £75,000 - £80,000 + 28 days holiday + Pension + Life Assurance + Private Healthcare

    Location: West London or Leeds – Hybrid working 1-2 days a week in the office.

    Duration: Permanent

    Apply NOW for an interview in the next week
National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.