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- Tasks: Analyse data to enhance user experience and drive audience growth across digital platforms.
- Company: Dynamic media organisation with a proprietary technology platform and global presence.
- Benefits: Competitive salary of £50K, hybrid working, and great career development opportunities.
- Why this job: Join a forward-thinking team and make a real impact on digital content experiences.
- Qualifications: Experience in data analysis, AB testing, and strong SQL skills required.
- Other info: Collaborative environment with opportunities to work on innovative projects.
The predicted salary is between 36000 - 60000 £ per year.
A media organisation which owns and operates a proprietary technology platform which enables the creation, distribution and monetisation of digital content experiences. They own several leading brands and have offices in New York, London and Tokyo.
They are looking to recruit a Product Analyst to join their Owned and Operated team to work on the analysis of advancing subscription, engagement and audience analytics across their digital platforms. This will include enhancing paywall and registration performance, utilising AI to deliver a more local and personalised experience, supporting AB testing and delivering insights that drive audience growth, monetisation and retention. The Product Analyst will work closely with product, growth and editorial and will connect data with strategy - turning insights into product and content improvements that scale across the portfolio.
The Product Analyst will be required to contribute to the analytics roadmap, design, implement and evaluate AB tests to enhance aspects of user experience. Lead analytics on first-party data initiatives, collaborate on forecasting for 2026 and build infrastructures to measure LTV by acquisition source. You will also develop deep-dive reporting and insights on content consumption and support evaluation of AI-driven metadata features. Develop, maintain and evolve self-service dashboards across Tableau/Looker for O&O teams - covering traffic, content, SEO and newsletter performance.
What you’ll need to succeed:
- Experience of working in a Data Analysis/Product Analyst capacity
- Experience of AB Testing
- Strong experience in SQL - ideally with BigQuery
- Knowledge of GA4 (Google Analytics) or Adobe Analytics
- Familiarity with subscription and user lifecycle metrics - CAC, churn, CLV, LTV, retention cohorts
- Experience building automated dashboards and data pipelines
- Ability to translate complex data into clear insights and recommendations for non-technical teams
- Experience gained in media, e-commerce or subscription businesses
What you’ll get in return:
- £50K benefits
- Hybrid working - 2-3 days in the office
If you’re interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now. If this job isn’t quite right for you, but you are looking for a new position, please contact us for a confidential discussion about your career.
Product/ Data Analyst employer: HAYS Specialist Recruitment
Contact Detail:
HAYS Specialist Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Product/ Data Analyst
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at the company you're eyeing. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Prepare for the interview by diving deep into the company's products and analytics. Show them you know their stuff and how you can contribute to enhancing user experience and driving audience growth.
✨Tip Number 3
Practice your data storytelling skills! Be ready to explain complex insights in a way that even non-tech folks can understand. This will set you apart as a candidate who can connect data with strategy.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to engage with us directly.
We think you need these skills to ace Product/ Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Product/Data Analyst role. Highlight your experience with data analysis, AB testing, and any relevant tools like SQL or Google Analytics. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific projects where you've used data to drive insights or improvements. Whether it's enhancing user experience or building dashboards, we love seeing real examples of your work that demonstrate your impact.
Keep It Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for easy reading and avoid jargon unless necessary. We appreciate straightforward communication that gets to the heart of your qualifications.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you're keen on joining our team at StudySmarter!
How to prepare for a job interview at HAYS Specialist Recruitment
✨Know Your Data Tools
Make sure you're well-versed in SQL, especially with BigQuery, as this role heavily relies on it. Brush up on your knowledge of GA4 or Adobe Analytics too, so you can confidently discuss how you've used these tools to drive insights in previous roles.
✨Showcase Your AB Testing Experience
Be prepared to talk about your experience with AB testing. Have specific examples ready where you've designed, implemented, and evaluated tests that led to measurable improvements in user engagement or monetisation.
✨Connect Data to Strategy
This role is all about turning data into actionable insights. Think of examples where you've successfully connected analytics to product or content strategies. Be ready to explain how your insights have driven growth or retention in past projects.
✨Prepare for Technical Questions
Expect some technical questions during the interview. Brush up on subscription and user lifecycle metrics like CAC, churn, and LTV. Being able to discuss these concepts clearly will show that you understand the business side of data analysis.
