Data Scientist

London
7 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist - New

Data Scientist/AI Engineer

Data Scientist (Globally Renowned Retail Group)

Data Scientist - (6-12 Months)

๐Ÿ“ London, N1 9GU | Hybrid Working

๐Ÿ•’ Start Date: July 2025

Are you a talented Data Scientist looking to make an impact in a and influential organisation? This is an exciting opportunity to use your analytical expertise and machine learning skills to enhance audience engagement strategies, improve user experience, and drive innovative solutions.

๐Ÿ”Ž About the Role

You'll be working across diverse teams, Editorial, Marketing, Sales, Product, and Engineering, to develop improving-edge models, generate meaningful insights, and ensure data-driven decision-making. Your work will contribute directly to the organisation's mission of informing and engaging audiences.

โœจ Key Responsibilities

Use advanced data analytics techniques to uncover audience behaviour trends
Develop predictive models and machine learning algorithms to enhance decision-making
Collaborate with cross-functional teams to shape data-driven solutions
Design and conduct experiments, refining models for continuous improvment
Enhance data infrastructure and tools for streamlined ML lifecycle management
Present complex findings in an accessible way for technical and non-technical stakeholders
Ensure ethical data handling and compliance with privacy regulations

๐Ÿ“Œ What We're Looking For

โœ… An advanced degree in Statistics, Mathematics, Physics, Computer Science, or a related field

โœ… At least two years of experience in Machine Learning

โœ… Strong proficiency in Python (NumPy, Pandas, Scikit-Learn) and SQL

โœ… Experience with deep-learning frameworks like TensorFlow and PyTorch

โœ… Knowledge of cloud services (AWS, Google Cloud) and productionising ML models

โœ… Ability to conduct successful A/B and multivariate tests

โœ… A keen curiosity and proactive approach to problem-solving

We Are Aspire Ltd are a Commited employer

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.

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? Youโ€™re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market โ€” it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

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

Machine learning job adverts in the UK love vague phrases like โ€œstrong mathsโ€ or โ€œsolid fundamentalsโ€. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.