dunnhumby
Retail
Price&PromotionSeniorAnalyst
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“Price & Promotion Senior Analyst at dunnhumby”
Industry & Context.
Full Job Description
dunnhumby is the global leader in Customer Data Science, partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value for their customers. dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Nestlé, Unilever and Metro. We’re looking for a talented Price and Promotion Senior Analyst. Use your insights from dunnhumby’s tools, analysis and consultancy to create and deliver client presentations and reports that provide insights and solutions that add measurable value to the retail. Support the creation of high-quality deliverables in the Price & Promotion workplan for the retail. Follow up the execution and measurement of pricing and promo recommendations by products, categories and campaigns to drive improvement and change management based on what's important to customers and retail. Demonstrate good knowledge of the Price & Promotion strategy of the retailer client and their business in order to advise in line with their strategies and to optimize the value we offer. Work collaboratively with P&P capability leaders to share and apply trends and best practices to spot and work on opportunities together with Retail. What we expect from you: Good knowledge of pricing and promotions and retail industry Al least 5 years of proven experience in pricing or promotions or both in retail Very passioned of data science to improve the lives of customers through optimal pricing and promotional decisions in retail. Strong client relationship and stakeholders' engagement skills High consultancy and project management skills Great analytical skills, data-driven approach to draw clear conclusions and recommendation from large datasets Advance in excel and power BI. Desirable proficien
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