Our Team: How we enrich everyday life
You’ll be joining the team behind some of the UK’s biggest and most loved radio competitions, including Make Me A Winner. Sitting within the Consumer Competitions Data team you’ll be responsible for reporting on and helping colleagues drive revenue delivery and operational excellence.
The Difference you will make
As Senior Data Analyst, you’ll be the go to person for understanding how listeners and customers engage with our competitions across multiple channels – from SMS and online forms to app and web entries.
Using SQL you’ll turn raw entry and revenue data into clear stories about customer behaviour, preferences and trends, helping the team optimise mechanics, prize strategies, marketing and pricing. You’ll work closely with product, marketing, commercial and content colleagues to make sure our competitions are driving both audience engagement and revenue.
Your role
1. Use SQL (. Redshift) to extract and transform competition and customer data.
2. Build and maintain dashboards (. in Power BI/Tableau).
3. Analyse competition entry behaviour across channels (. SMS, online, app, web).
4. Identify customer segments and trends in competition formats, prize types, price points and entry patterns.
5. Build and maintain views of customer lifecycle and frequency.
6. Evaluate mechanics and recommend changes to improve engagement and ROI.
7. Own regular reporting on competition performance: entries, unique players, conversion,
8. Design and analyse tests (. different price points, copy, prize types, entry limits).
9. Provide clear recommendations on what to scale, stop or refine based on data.
10. Partner with SMEs in the Consumer Competitions team to understand their questions and turn them into clear analytical briefs.
11. Present insights and recommendations in a straightforward, non-technical way – focusing on “so what” and “what next”.
The Skills you will bring
12. Significant experience as a data/BI/insight analyst using SQL.
13. Strong SQL skills, comfortable working with large transactional datasets.
14. Experience with at least one BI/visualisation tool (. Power BI, Tableau).
15. Experience analysing customer behaviour, segmentation, funnels or lifecycle metrics.
16. Good grasp of statistics (. A/B testing, significance, basic regression/propensity).
17. Excellent communication skills – able to tell a clear story with data.
Working Pattern/Location
This is a full-time role, Monday – Friday, 37.5 hours a week. We also support a hybrid working model that balances working from home and our office in Manchester (Castle Quays)