Data Scientist - Retail and Luxury

FreshMinds Talent
London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist - New

Data Scientist - Imaging - Remote - Outside IR35

Data Scientist - Workforce Modelling

Data Scientist (Predictive Modelling) – NHS

A global lifestyle brand is hiring a Data Scientist to join the team. You will report to the Director of Global Customer Data Science and work on developing predictive models and customer segmentation strategies to enhance personalised experiences and improve CRM effectiveness.

Responsibilities

Develop and implement predictive models to understand customer behaviour Create customer segmentation using behavioural, transactional, and demographic data Design and build models to enhance personalised experiences across channels Collaborate on test & learn methods to measure CRM initiatives Monitor and optimise model performance Transform analytical solutions into production-ready code Implement models within existing technology stack Ensure scalability and efficiency of deployed solutions Translate complex findings into actionable insights Create data visualisations to communicate patterns Partner with cross-functional teams to enhance CRM strategies Provide data-driven recommendations to improve engagement metrics


Requirements


Experience in Customer Marketing Data Science, including applied statistics and machine learningProficiency in Python and ML libraries (e.g. pandas, numpy, scikit-learn, tensorflow, pytorch)Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, DatabricksExperience with ML Ops, including deployment and monitoringAbility to work cross-functionally with marketing, CRM, and engineering teamsExcellent communication skillsExperience in a global or multi-regional context is a plus

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.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.