Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Digital Marketing Data & Pricing Analyst (B2C Aggregators)

Nottingham
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

FMCG Product Insights and Commercial Data Analyst

Data Analyst

Affiliate Data Analyst

Data Analyst - Customer Growth (D2C) - AJ Bell

Senior Growth Data Scientist

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 Details

Leading UK financial services company

Description

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. 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 insight
A great attention to detail and be process-oriented to review, suggest and implement improvements where appropriate
Able to work in a fast paced, changing environment

Profile

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 insight
A great attention to detail and be process-oriented to review, suggest and implement improvements where appropriate
Able to work in a fast paced, changing environmentJob Offer

Opportunity to influence and enhance marketing insight & analytics strategy

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 Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.