Senior Analyst – Customer Health

The Role: 

Utilise advanced analytical techniques to understand customer behaviour, identify opportunities across acquisition, retention, loyalty and customer value, and turn data into recommendations that improve business decision-making.

WHATS IN IT FOR YOU:

• 40% staff discount plus friends & family discounts throughout the year
• Access to our reward platform for external discount and offers
• Private pension scheme
• Virtual GP access for you and your children – it allows you to speak to a doctor at a time and date that suits you
• All employees are covered by our life assurance policy from day one
• Unlock extra leave with our buy more holiday scheme.
• Celebrate YOU! Enjoy an extra paid day off on your birthday each year
• Enhanced maternity, paternity and adoption leave, and shared parental leave (eligible after 2 years’ service).
• Spread the cost of your commute with interest-free season ticket loans
• Do your bit for the environment and save money with our Cycle2Work scheme
• We're proud to partner with the Retail Trust and Fashion & Textile Children's Trust

What you’ll be doing:

• Data Mining: Use data mining techniques to combine multiple large customer, transaction, campaign and digital datasets into new data marts, analytical models and reusable insight assets.
• Descriptive Analytics: Interpret data and present findings to stakeholders in a clear and impactful manner to drive data-driven decision making. Deliver deep-dive customer insight and recommendations that explain customer performance and behavioural trends.
• Advanced Analytics: Apply statistical and analytical techniques such as segmentation, clustering, predictive modelling and campaign measurement. Working knowledge of data science techniques including random forest, k-means and linear regression.
• Optimisation: Collaborate with cross-functional teams to identify opportunities for optimisation. Support initiatives across customer acquisition, retention, loyalty, lifecycle and marketing performance.
• Collaborate: Support a given analytical principle and deliver an agreed analytics strategy. Create stakeholder-ready dashboards, reporting and insight packs while ensuring outputs are accurate, documented and governed.
• Development: Stay updated on industry trends and best practices in customer analytics, loyalty, CRM, marketing measurement and analytical techniques.
• Analytical mindset: Customer-focused mindset with the ability to think critically, challenge assumptions and solve complex business problems through data.
• Attention to detail: Ensure accuracy, consistency and reliability of analytical findings, maintaining high standards of quality and governance.
• Commercial curiosity: Demonstrate a strong interest in customer behaviour and how it impacts sales, loyalty, retention, profitability and long-term customer value.
• Clear communicator: Translate complex analytical concepts and findings into clear, impactful recommendations for both technical and non-technical stakeholders.
• Continuous learning: Proactively seek opportunities to expand analytical, technical and customer knowledge, staying up to date with emerging best practices.
• Strong Opinions Loosely Held: Be vocal and maintain your point of view while remaining open to new ideas, challenge and opposing perspectives.

Who you are:

• Proficiency in statistical analysis, customer analytics and data visualisation tools. Experience working with large customer, marketing, loyalty or digital datasets. (3+ years)
• Proven experience writing code in languages such as SQL, Python or R.
• Experience applying advanced analytical techniques including segmentation, regression analysis, clustering, predictive modelling and campaign measurement. Knowledge of data science and machine learning techniques such as random forest, k-means and linear regression.
• Strong communication, presentation and data storytelling skills, with the ability to translate complex analytical findings into clear and commercially relevant recommendations.
• Good understanding of customer profiling, customer value, customer lifecycle measurement and behavioural analytics.
• Experience creating stakeholder-ready dashboards, reporting solutions and insight packs using data visualisation tools.
• Knowledge of data quality, governance, documentation standards and ethical use of customer data.
• Insight quality and impact. Timely delivery. Stakeholder satisfaction. Adoption of customer insights and outputs. Development of analytical capability.