Marketing Data Analyst (Mid-Senior Level)

HelloKindred
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Customer Campaign Data Analyst - B2C

Finance Data Analyst

Data Scientist - Measurement Specialist

Data Scientist - Measurement Specialist

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.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.