Senior Marketing Analyst

Keynsham
1 year ago
Applications closed

Related Jobs

View all jobs

Marketing Data Analyst - Hybrid, Impact & Insights

Mobile App Marketing Data Analyst

French Data Analyst

Senior Data Scientist: Causal Analytics for Marketing AI

Senior Data Analyst (GTM)

Senior Consultant - Data Analyst

Drive Marketing Insights with PowerBI on marketing data science projects!

Collaborate with senior marketing stakeholders to shape data-driven strategies
Flexible, remote-first role with opportunities for professional development
Use modern analytics tools and build insights for high-impact B2B campaignsAre you a data-driven storyteller passionate about translating data into actionable insights for marketing? This Senior Analyst role is perfect for a technical analyst skilled in PowerBI, Python, SQL, and modern data platforms who wants to make a tangible impact on B2B marketing campaigns. Working closely with senior stakeholders, you’ll be part of a strategic reporting team delivering insights that shape critical marketing decisions.
 
What you’ll be doing:
As a Senior Analyst, you’ll report into the Strategic Reporting team. You’ll be responsible for building dynamic PowerBI dashboards that transform complex data into compelling narratives for their marketing team. You’ll come in as a statistically driven, marketing data analyst to work across data science projects where you’ll focus on querying data, creating analytics, and generating reports that bring marketing campaigns to life.
 
You’ll play an active role in helping marketing teams understand campaign performance, crafting stories with data, and delivering insights directly to high-level stakeholders, including the Head of Marketing. With the opportunity to grow into data science, you’ll explore using Python for predictive analytics and advanced modelling, making this a fantastic opportunity for career progression.
 
What experience you’ll need to apply:

Experience in Marketing Data Analytics
Solid experience in data analysis and visualization with a focus on PowerBI and SQL
Ability to query datasets, analyse B2B marketing metrics, and deliver engaging reports
Working knowledge of Python with a foundation in statistical modelling and classification techniques
Familiarity with Google Analytics, PPC/SEO data, and other marketing tools such as HubSpot, Hootsuite, and Salesforce
Proven ability to work with senior stakeholders and present data-driven recommendations
Passion for marketing analytics and a knack for storytelling with data 
What you’ll get in return:
A salary up to £45,000 annually, with 25 days of annual leave (plus options to purchase additional days), private healthcare, GP services for you and household members, and access to a share-save scheme. You’ll also have comprehensive learning support, including a fully equipped training provider and other tech development resources
 
The role requires one day a week in Bristol, with occasional travel to London (around once a month, which would be paid for). This is a set requirement and this role cannot be offered fully remotely.
 
What’s next?
Apply with your updated resume, and we’ll review your application as soon as possible to set up a call and discuss the role further

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 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.

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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.