Senior Marketing Data & Pricing Analyst (B2C Digital Channels)

Michael Page

Nottingham

1 year ago

Applications closed

Related Jobs

View all jobs

Senior Data Analyst - UK

Data Analyst

Data Analyst – Automotive Industry

Senior Data Analyst

Senior Data Scientist - Forecasting

Commercial Data Analyst

Leading UK financial services company require a Senior Digital Marketing & Customer Data Analyst to enhance their customer and marketing analytics capabilities. You will be joining at a key growth point in the organisation and work with an existing team of Data Analysts to increase adoption of technology and analytics tools to aid strategic decision making and increase ROI. Client DetailsLeading UK financial services company DescriptionLeading UK financial services company require a Senior Digital Marketing & Customer Data Analyst to enhance their customer and marketing analytics capabilities. You will be joining at a key growth point in the organisation and work with an existing team of Data Analysts to increase adoption of technology and analytics tools to aid strategic decision making and increase ROI. You will work with the CRM team and 3rd Party aggregators to enhance customer profiling and maximise marketing channels pricing strategy.The role has a highly flexible hybrid / remote working environment.Core Responsibilities:Analyse live and historical data to provide insight and recommendations to maintain optimal performance, budget allocation / ROI across multiple channels to improve conversion rates.Analyse various data and factors to recommend the best pricing strategy for a business.Conduct detailed analysis and trend reporting to identify patterns and insights that inform long term business strategies.Daily/Weekly/Monthly reporting on market trends, customer behaviour, and campaign performance.Track key performance indicators (KPIs) related to customer engagement and satisfaction and provide insight, along with recommendations to drive improvements in them.Strong presentation skills, including the ability to translate complex data into understandable insight.Build and manage external relationship with Lead Generating partners as required. Requirements:Experience in the Financial Services Industry (Essential)Experience working with large data sets, Excel and SQL proficiency (Essential)Experience using Salesforce and data visualisation tools (Power BI / Tableau Preferable)Degree in relevant subject (Business, Mathematics, Economics or similar degree) (Preferable)Strong presentation skills, including the ability to translate complex data into understandable insightA great attention to detail and be process-oriented to review, suggest and implement improvements where appropriateAble to work in a fast paced, changing environment ProfileExperience in the Financial Services Industry (Essential)Experience working with large data sets, Excel and SQL proficiency (Essential)Experience using Salesforce and data visualisation tools (Power BI / Tableau Preferable)Degree in relevant subject (Business, Mathematics, Economics or similar degree) (Preferable)Strong presentation skills, including the ability to translate complex data into understandable insightA great attention to detail and be process-oriented to review, suggest and implement improvements where appropriateAble to work in a fast paced, changing environmentJob OfferOpportunity to influence and enhance marketing insight & analytics strategy

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

Industry Insights

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

Jan 18, 2026

Careers Jobs

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? You’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.

Jan 13, 2026

Jobs

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 — 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.

Jan 6, 2026

Education Jobs

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 “strong maths” or “solid fundamentals”. 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.