National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Digital Data Analyst (Finance)

Hybrid
Bath
2 days ago
Create job alert

We are seeking a detail-oriented Digital Data Analyst to oversee the financial performance of our paid media campaigns. This role involves analysing advertising spend, optimizing budgets, and ensuring maximum return on investment (ROI) across various digital platforms.Ready to turn billions of impressions into measurable impact?We’re looking for a sharp, analytical mind who can dive into client media spend, performance data, and surface clear, actionable insights that drive real value.As our Digital Data Analyst, you’ll be the go-to expert for ensuring our paid media campaigns (spanning Meta, AdWords and more) deliver exactly what they promise—on target, on budget, and with tangible returns. You’ll consolidate complex data into compelling narratives, manage media plans to meet forecasted outcomes, and work directly with revenue and delivery teams to ensure spend and performance are always aligned.This is a role for someone who doesn’t just understand data—but knows how to tell its story.Key Responsibilities:Financial Analysis & Budgeting: Monitor and analyse paid media expenditures, ensuring cost efficiency and alignment with financial goals.Performance Tracking: Evaluate campaign effectiveness using key financial metrics such as CPC (Cost per Click), CPA (Cost per Acquisition), and CTR (Click-Through Rate).Data-Driven Insights: Provide actionable recommendations based on financial data to optimize media spend and improve campaign performance.Forecasting & Reporting: Develop financial models to predict future media spend and revenue impact. Prepare detailed reports for stakeholders.Collaboration: Work closely with Strategic Partnership, Digital and finance teams to align media strategies with business objectives.Market & Competitor Analysis: Research industry trends and competitor strategies to identify opportunities for cost-effective media investments.Required Skills & Qualifications:Proven experience in paid media analytics, financial modelling, and digital advertising.Strong proficiency in Excel, Google Analytics, and media buying platforms (Google Ads, Meta Ads, etc.).Ability to interpret complex financial data and translate insights into strategic recommendations.Excellent communication and presentation skills.Detail-oriented with strong problem-solving abilities.Preferred Qualifications:Experience with SQL or Power BI for data visualization.Knowledge of advertising and attribution modelling.

Related Jobs

View all jobs

Digital Data Analyst (Finance)

Digital Data Analyst (Finance)

Digital Data Analyst

Reinsurance Digital & Data Analyst

Data Analyst

AI and Data Analyst...

National AI Awards 2025

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 to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.