Customer Insight Analyst (SQL/SAS/Tableau)

Company Name: Burberry Limited

Location: Taikoo Shing, Not, HK

Overview
INTRODUCTION

 

Founded in 1856, Burberry today remains quintessentially British, with outerwear at its core.  Digital luxury positioning and intensive focus on design innovation, quality and heritage icons ensure continued brand purity and relevance globally across genders and generations. Burberry believes that in order to be a great brand it must also be a great company and constantly leverages the energy of its compassionate and creative thinking culture to continually innovate and drive the brand forward. Headquartered in London, Burberry is a design, marketing and retail led business with a global reputation for innovative product design, digital marketing initiatives and dynamic retail strategies.

RESPONSIBILITIES

 

  • Their key responsibility will be to extract, visualise, and analyse both internal and external customer data to understand customer behaviour and business KPIs in order to drive commercial performance in both the short and long term. This will involve working closely with stakeholders across the business (Strategy, Merchandising, Planning, Marketing, S&P, Operations) to incorporate insight and propose recommendations on actionable business opportunities.
  • They will also develop and manage a suite of analytical tools to track key Customer KPIs and commercial performance, to inform strategic and operational decision making on an on-going basis for senior leadership.
  • Partnering with corporate and regional insight teams they will share best practices across our global teams, working as a single point of contact to ensure alignment.
PERSONAL PROFILE

 

  • High Calibre Graduate with a strong analytical and commercial mind set.
  • 1-2 years work experience preferred but it is an equal opportunity for high calibre graduate students.
  • Advanced Excel skills.
  • Experience in using SQL or SAS for data processing
  • Knowledge of Tableau is a plus
  • Knowledge of statistical techniques (multivariate data analysis, predictive modelling) preferred.
  • Ability to understand customer data and communicate it in a concise and relevant way to various stakeholders.
  • Strong time management skills and ability to handle and prioritise multiple requests.