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For Companies At a Glance
- Tasks: Analyse data and generate insights for digital marketing campaigns across various platforms.
- Company: Join a dynamic European marketing team driving performance across multiple markets.
- Benefits: Enjoy a flexible work environment with potential for contract extension and growth opportunities.
- Why this job: Be part of a collaborative culture that values data-driven decisions and innovation.
- Qualifications: 3-5 years in digital marketing or paid media analytics required.
- Other info: Opportunity to work with cutting-edge tools and large datasets.
The predicted salary is between 36000 - 60000 £ per year.
Job Description
JOB TITLE: Paid Media Analyst
REFERENCE: To be added by HR
LOCATION: Surrey, UK
CONTRACT TYPE: 6-month fixed-term (with possibility of extension)
REPORTING TO: Paid Media Operations Lead
EXPERIENCE LEVEL: 3–5 years in data-led digital marketing or paid media analytics
WORKING HOURS: 37.5 hours per week (some out-of-hours work may occasionally be required during key campaigns or urgent situations)
ABOUT THE ROLE
We’re looking for a skilled Paid Media Analyst to join a centralised European marketing team that supports multiple markets across the region. This role focuses on delivering performance insights, campaign reporting, and optimisation strategies across a range of paid digital channels.
You’ll work with large datasets to create meaningful dashboards, ensure data integrity, and generate insights that drive media efficiency across channels such as paid search, social, display, programmatic, and video.
KEY RESPONSIBILITIES
Analytics & Insights
- Generate actionable insights across key digital platforms (e.g., Google, Meta, TikTok, Amazon, affiliates).
- Build and maintain dynamic dashboards using tools like Looker Studio or other BI platforms.
- Validate data inputs and outputs; lead on user testing to ensure data quality.
- Conduct in-depth post-campaign analysis to uncover key performance drivers and learning points.
- Identify data opportunities to enhance campaign strategies and support planning decisions.
- Use test-and-learn frameworks (e.g., A/B testing) to measure campaign impact and efficiency.
- Collaborate with internal teams to ensure insight outputs align with business goals.
Reporting & Visualisation
- Develop clear, intuitive dashboards for internal and external stakeholders.
- Translate business requirements into scalable and automated reporting frameworks.
- Monitor data accuracy, troubleshoot issues, and escalate problems where necessary.
- Continuously refine reporting tools based on feedback and evolving KPIs.
- Support with campaign setup and reporting administration across markets.
Paid Media Analyst employer: Bodhi
Contact Detail:
Bodhi Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Paid Media Analyst
✨Tip Number 1
Familiarise yourself with the key digital platforms mentioned in the job description, such as Google, Meta, and TikTok. Understanding their analytics tools and how they operate will give you a significant edge during interviews.
✨Tip Number 2
Brush up on your skills in data visualisation tools like Looker Studio or other BI platforms. Being able to demonstrate your ability to create dynamic dashboards will show that you're ready to hit the ground running.
✨Tip Number 3
Prepare examples of past campaigns where you've used A/B testing or similar frameworks to measure impact. This will help you illustrate your analytical skills and how you've contributed to campaign success in previous roles.
✨Tip Number 4
Network with professionals in the digital marketing field, especially those who work with paid media. Engaging with industry peers can provide insights into current trends and may even lead to referrals for the position.
We think you need these skills to ace Paid Media Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data-led digital marketing and paid media analytics. Use specific examples of past campaigns you've worked on, focusing on your role in generating insights and optimising performance.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your skills align with the key responsibilities, such as building dashboards and conducting post-campaign analysis. Be sure to include any experience with tools like Looker Studio.
Showcase Analytical Skills: Provide concrete examples of how you've used data to drive decisions in previous roles. Discuss any A/B testing frameworks you've implemented and the impact they had on campaign efficiency. This will demonstrate your analytical mindset.
Proofread Your Application: Before submitting, carefully proofread your application materials. Check for any spelling or grammatical errors, and ensure that all information is clear and concise. A polished application reflects your attention to detail, which is crucial for a Paid Media Analyst.
How to prepare for a job interview at Bodhi
✨Showcase Your Analytical Skills
As a Paid Media Analyst, your ability to analyse data is crucial. Be prepared to discuss specific examples of how you've generated actionable insights from large datasets in previous roles. Highlight any tools you've used, such as Looker Studio or other BI platforms.
✨Demonstrate Your Knowledge of Digital Platforms
Familiarise yourself with the key digital platforms mentioned in the job description, like Google, Meta, and TikTok. Be ready to talk about your experience with these platforms and how you've optimised campaigns across them.
✨Prepare for Technical Questions
Expect technical questions related to data validation, dashboard creation, and reporting frameworks. Brush up on your knowledge of A/B testing and be ready to explain how you've applied these concepts in past campaigns.
✨Emphasise Collaboration Skills
This role involves working closely with internal teams. Prepare to discuss how you've collaborated with others to align insights with business goals. Share examples of successful teamwork and how you communicated complex data findings to non-technical stakeholders.
