Data Science Manager – Insights Consultancy

Resources Group
City of London
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Data Science Manager - Market Research Consultancy

Data Science Manager

Senior Data Scientist / Machine Learning Engineer

Data Science Consultant - Health

Copy of Graduate Data Science Consultant

CD00649687

Data Science Manager – Insights Consultancy

To £65,000; London (Hybrid working)

Data Science Manager sought by the highly visible Data Science team of this leading global insights consultancy in a key, client facing role.


The Data Science Team here covers numerous segmentation and conjoint led insights projects, grounded in survey data, and working closely with consulting teams and clients in so doing – but they are also involved in wider corporate initiatives where data science input is required too. Clients are typically large consumer brands, public bodies, government and leading not-for-profit organisations.


In joining this hugely successful team you’ll bring client facing skills, technical and coding prowess to compliment a team made up of skilled Data Scientists from market research backgrounds. You’ll therefore be a Data Scientist who alongside knowledge of surveys and segmentation, also has good skills in Python (and R), machine learning, Bayesian methods, text analytics and more. Previous work in market research/insights in a data science/analytics capacity is essential re helping to develop the team’s overall innovative approach to insights led data science approaches.


If you’re keen to be a Data Science Manager in a research agency that will give you client exposure, and value and develop you further (relocation and/or sponsorship [including sponsorship post visa expiry] is not available at this time), contact Carl at Resources Group


About Resources Group:


With over thirty years’ experience helping thousands of Researchers, Insight Specialists, Marketers and Data Analysts in their career moves, no one has better knowledge of the Market Research, Insights and Marketing Strategy job market than Resources Group. Our consultants take the time to understand your career aims and are dedicated to providing impartial advice and finding you the best career move, with access to an unrivalled range of opportunities with top employers in the sector - visit our website for many more options!


Resources Group’s Diversity and Equality Policy determines that we submit applicants to our clients on the basis of merit and ability, regardless of race, colour, age, disability, family responsibilities, gender, marital status, nationality, religious or political views or affiliations, sexual orientation or socio-economic background.

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 Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.