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About the Role
Utilize advanced analytical techniques to support Range, Space, Price & Promotion decisions, combining customer, product, pricing and commercial data to identify opportunities that improve demand, margin, stock efficiency and customer relevance.
Responsibilities
- Use data mining techniques to combine multiple large product, transaction, customer, pricing and store datasets into new data marts, analytical models and reusable insight assets.
- Interpret data and present findings to stakeholders in a clear and impactful manner to drive data-driven decision making.
- Deliver deep-dive commercial insight and recommendations that explain product, pricing, promotional and trading performance.
- Apply statistical and analytical techniques such as forecasting, clustering, elasticity analysis and promotional measurement.
- Collaborate with cross-functional teams to identify opportunities for optimisation.
- Support initiatives across ranging, store space allocation, pricing strategy, promotional effectiveness and trading performance.
- 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.
- Stay updated on industry trends and best practices in retail analytics, ranging, pricing, promotions, forecasting and analytical techniques.
Requirements
- Proficiency in statistical analysis, commercial analytics and data visualisation tools.
- Experience working with product, pricing, promotional, customer and store datasets.
- Proven experience writing code in languages such as SQL, Python or R.
- Experience applying advanced analytical techniques including forecasting, regression analysis, clustering, elasticity analysis and promotional 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 pricing strategy, promotional effectiveness, demand forecasting, stock productivity and retail performance measures.
- 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 business data.
Skills
- SQL
- Python
- R
- Forecasting
- Regression analysis
- Clustering
- Elasticity analysis
- Promotional measurement
- Random forest
- K-means
- Linear regression
- Data visualisation
Location
- UK
Work Type
- Full-time
Experience Level
- 3+ years
Benefits
- 40% staff discount plus friends & family discounts throughout the year
- Access to our reward platform for external discount and offers
- Private pension scheme
- Option to join our Healthcare Private Medical Scheme
- Virtual GP access for you and your children
- All employees are covered by our life assurance policy from day one
- Unlock extra leave with our buy more holiday scheme.
- 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)
- Interest-free season ticket loans
- Cycle2Work scheme
About the Company
- Feel-good fashion brand making style accessible and fun for over 55 years.
- We care about you and the planet and believe fashion should be a force for positive change.
- We celebrate inclusion and diversity in everything we do.
- We’re proud of our inclusive culture and our talented team members who embrace our shared purpose, behaviours and values.
- We prioritise development, offering training to support your progression, so you can be your absolute best and achieve your goals.
- We pride ourselves on being a flexible employer, our colleagues work a range of patterns.
Equal Opportunity
- We celebrate inclusion and diversity in everything we do.