Marketing Data Analyst (Mid-Senior Level)

HelloKindred
London
1 year ago
Applications closed

Related Jobs

View all jobs

Marketing Data Analyst - Hybrid, Impact & Insights

Junior Data Analyst: Digital Marketing Insights

Senior Data Analyst (Marketing Analytics)

Senior Marketing Data Analyst - Hybrid | PowerBI & GA4

Remote-First Data Analyst — Tableau Dashboards & Insights

Mobile App Marketing Data Analyst

Job Description

Work set-up:Remote, supporting the EUR time zone  (UK or EUR is ideal), 2-3 month contract

Our client in the information technology, consulting, and outsourcing industry is seeking a Marketing Data Analyst who will play a pivotal role in the marketing team by gathering, analyzing, and interpreting data to generate actionable insights that will inform strategic decisions. This mid-senior level position requires expertise in marketing analytics, strong data analysis capabilities, and proficiency in relevant tools. Collaboration across cross-functional teams to optimize marketing strategies and campaign performance is essential.

What you will do:

  • Partner with seasoned marketers and ABM leaders to analyze performance data, extract insights, and recommend actionable strategies for improvement.
  • Collect, clean, and analyze datasets from marketing channels such as Paid Advertising (LinkedIn, Display Ads), Web, Email (Pardot), Social, Content Platforms (Turtl, Foleon, Uberflip), and CRM (Salesforce) to assess campaign effectiveness and customer behavior.
  • Strategize, plan and develop dashboards and regular reports to track performance against KPIs, including customer acquisition cost, ROI, and conversion rates as well as make recommendations on dashboards required. Report against measurement criteria set for the Reputation, Relationships, and Revenue (RRR) Strategy.
  • Assess marketing campaign effectiveness, identify trends and opportunities, and collaborate with teams to adjust strategies based on data insights.
  • Use tools like Tableau, Power BI, and Google Data Studio to create clear, engaging data visualizations for stakeholders at all levels.
  • Conduct advanced statistical analysis and A/B testing to evaluate marketing activities. Track web traffic, customer behavior, and engagement using tools like Google Analytics and Adobe Analytics.
  • Cross-Functional Collaboration: Work with marketing, sales, product, and finance teams to ensure data insights align with business goals and are effectively shared across teams.
  • Keep up with industry trends, tools, and best practices in marketing analytics to improve processes and strategies.
  • Translate marketing data into compelling narratives that inform and influence stakeholders.


Qualifications

  • Bachelor’s degree in marketing, Data Analytics, Business, Economics, or related fields.
  • Professional certifications (e.g., Google Analytics, Tableau) are mandatory.
  • 8 -10+ years in marketing analytics or data analysis roles. Familiarity with digital marketing channels such as PPC, SEO, and email marketing is strongly preferred.
  • Proficiency in Excel, SQL, and Google Analytics.
  • Experience with data visualization tools like Tableau, Power BI, and Google Data Studio.
  • Familiarity with statistical tools such as R, Python, or SPSS is a plus.
  • Experience with A/B testing tools (e.g., Optimizely, Google Optimize) is a plus.
  • Demonstrated ability to interpret complex data and provide actionable insights.
  • Strong written and verbal skills to present data insights to technical and non-technical audiences.
  • Accuracy in handling large datasets and ensuring data integrity.



Additional Information

Candidates must be legally authorized to live and work in the country the position is based in, without requiring sponsorship.

We appreciate your interest in this opportunity. Please note only applicants selected for an interview will be contacted.

HelloKindred is proud to be an equal opportunity employer, committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, gender identity/expression, sexual orientation, national origin, disability, age, or veteran status.

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 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.

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.