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For Companies At a Glance
- Tasks: Drive revenue insights and optimise pricing strategies using data analytics.
- Company: Join Vintage Cash Cow, a data-driven company transforming customer journeys.
- Benefits: Full-time role with opportunities for growth and collaboration in a dynamic team.
- Why this job: Make a real impact on revenue decisions and work with cutting-edge data tools.
- Qualifications: Expert SQL skills and experience with BI tools required.
- Other info: Be part of a curious team focused on continuous improvement and innovation.
The predicted salary is between 36000 - 60000 £ per year.
About the team: At Vintage Cash Cow, data is how we scale impact. Every customer journey, from sending in pre-loved items to getting paid, is informed by the insights we generate, the models we build, and the decisions we enable. Our Data team sits at the heart of this transformation, partnering closely with Technology & Product, and the wider business to turn information into action. We focus on building trusted, scalable data foundations and delivering insight that drives smarter decisions across the organisation. This is a team where curiosity meets craft: blending analytical thinking, technical excellence, and a strong commercial mindset to deliver insight that feels clear, useful, and future-focused.
About the role: We’re looking for a data-first, insight-hungry Data Analyst to help us deepen how data drives decisions across Vintage Cash Cow. You’ll own revenue analytics across our entire value chain. From acquisition pricing optimisation across diverse product categories to channel performance and sell-through strategy. Your work will directly influence how we price incoming goods, which sales channels we prioritise, and how we maximise margin across our multi-category, multi-channels business model. You won’t be starting from scratch, you’ll be joining an established, data-savvy team with strong foundations already in place. Our rebuilt modern data platform (FiveTran, Snowflake, dbt, Sigma) gives you everything you need to dive in fast and make an impact from day one.
Key Goals & Objectives
- Provide clear, accurate insight into revenue, margin, and performance drivers.
- Support pricing, forecasting, and growth decisions with high-quality analysis.
- Improve speed and confidence in commercial decision-making.
- Enable a culture of data-led revenue optimisation across the business.
Key Responsibilities & Skills
Revenue & Commercial Analytics:
- Own end-to-end revenue reporting and analysis across product categories and sales channels.
- Build predictive models for pricing optimisation, demand forecasting, and sell-through rates.
- Analyse category-level economics to identify margin opportunities and optimize acquisition pricing.
- Evaluate channel performance to inform strategic resource allocation.
- Partner with commercial teams on A/B testing for pricing strategies and channel experiments.
- Monitor and report on key revenue metrics: ASP by category, channel contribution margin, inventory turns, days to sale, etc.
Commercial Partnership
- Partner closely with stakeholders across the business to understand revenue goals.
- Translate complex analysis into clear commercial recommendations.
- Present insights that directly influence pricing, growth strategy, and operational decisions.
Continuous Improvement
- Contribute to developing data best practices, standards, and governance.
- Collaborate with engineers to improve data pipelines and performance.
- Stay curious, explore new BI tools, AI integrations, and analytical techniques that can enhance how we use data.
Essential Skills & Experience:
- Expert-level SQL skills with experience building complex data models for financial and commercial analysis.
- Experience with BI tools (Sigma, Power BI, Tableau, Looker, or similar).
- Solid understanding of modern data platforms (e.g. Snowflake, dbt, FiveTran).
- Strong communicator who can translate data into business impact.
- Strong commercial mindset, you care about revenue impact, not just outputs.
- Experience collaborating in cross-functional environments.
- Experience in e-commerce, marketplace, or re-commerce business models.
- Knowledge of pricing optimisation techniques or dynamic pricing strategies.
- Experience with experimentation frameworks (A/B testing, incrementality testing).
- Intermediate knowledge of Python for data analysis.
Senior Data Analyst (Revenue) in Morley employer: Vintage Cash Cow
Contact Detail:
Vintage Cash Cow Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Analyst (Revenue) in Morley
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Vintage Cash Cow. A friendly chat can sometimes lead to opportunities that aren’t even advertised!
✨Tip Number 2
Show off your skills! Prepare a portfolio or case studies showcasing your data analysis projects. When you get the chance to chat with hiring managers, having tangible examples of your work can really set you apart.
✨Tip Number 3
Be ready for the interview! Research common data analyst interview questions and practice your answers. Make sure you can explain your thought process behind your analyses and how they’ve driven business decisions.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Vintage Cash Cow team!
We think you need these skills to ace Senior Data Analyst (Revenue) in Morley
Some tips for your application 🫡
Show Your Data Passion: When you're writing your application, let your enthusiasm for data shine through! Share specific examples of how you've used data to drive decisions in previous roles. We love seeing that spark of curiosity and analytical thinking.
Tailor Your Application: Make sure to customise your application to reflect the key responsibilities and skills mentioned in the job description. Highlight your experience with SQL, BI tools, and any relevant projects that align with our revenue analytics goals. It shows us you’re serious about this role!
Be Clear and Concise: We appreciate clarity! When presenting your insights or experiences, keep it straightforward and to the point. Use bullet points if necessary to make your application easy to read. Remember, we want to see how you can translate complex data into clear recommendations.
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 gives you a chance to explore more about our team and culture while you’re at it!
How to prepare for a job interview at Vintage Cash Cow
✨Know Your Data Tools
Make sure you’re familiar with the data tools mentioned in the job description, like SQL, Snowflake, and dbt. Brush up on your skills and be ready to discuss how you've used these tools in past projects. This will show that you can hit the ground running!
✨Prepare Insightful Questions
Think of questions that demonstrate your understanding of revenue analytics and how it impacts business decisions. Ask about their current data strategies or how they measure success in revenue optimisation. This shows your curiosity and genuine interest in the role.
✨Showcase Your Analytical Mindset
Be prepared to discuss specific examples where your analytical skills made a difference. Whether it’s a predictive model you built or a pricing strategy you optimised, having concrete examples will help illustrate your capabilities and fit for the team.
✨Communicate Clearly
Practice translating complex data insights into simple, actionable recommendations. During the interview, focus on how you can communicate effectively with non-technical stakeholders. This is crucial for a role that requires collaboration across different teams.
