Data Scientist

INTRODUCTION

At Burberry, we believe creativity opens spaces. Our purpose is to unlock the power of imagination to push boundaries and open new possibilities for our people, our customers and our communities. This is the core belief that has guided Burberry since it was founded in 1856 and is central to how we operate as a company today.

We aim to provide an environment for creative minds from different backgrounds to thrive, bringing a wide range of skills and experiences to everything we do. As a purposeful, values-driven brand, we are committed to being a force for good in the world as well, creating the next generation of sustainable luxury for customers, driving industry change and championing our communities.

JOB PURPOSE

We are now recruiting for a Data Scientist to join the Customer Data Science team. The Customer Data Science team uses advanced modelling techniques to uncover our customers’ behaviours, preferences and intent to purchase. We aim to deliver targeted and personalised experiences across all customer touchpoints in collaboration with business stakeholders.

As a Data Scientist, you will be accountable for building and deploying robust statistical and machine learning models, exploring a wide range of new data sources, and generating reliable and actionable insights and recommendations. You will work closely with other data scientists and engineers to develop innovative solutions to use cases across the business related to the Burberry customer. Some examples of current work include:

- Propensity modelling: developing models to understand how likely a client or prospect is to purchase or interact with Burberry across multiple categories or time periods

- Product recommendations & discovery algorithms: Serving customers with tailored product recommendations throughout many brand touchpoints such as the website and emails.

- Client relationship intelligence: apply data-driven models and strategies to enable client advisors to build long-term engagement with their clients.

Are you a data scientist, or a recent graduate with an advanced degree in a quantitative field, and with a passion for using data, statistical modelling, machine learning and deep learning techniques to solve business problems and drive business value? If so, we’d love to hear from you.

RESPONSIBILITIES

• Generating robust advanced analytics and developing new cutting-edge machine learning models and data-driven tools to support our ongoing business strategy and drive future business performance
• Optimising and evolving the current models and analytics solutions that are in production, taking a test and learn approach and ensuring improvements are impactful and aligned to business objectives and strategyPresenting the analytics solutions, models and insights to a range of business stakeholders and contributing to strategic decisions
• Designing, evaluating and encouraging experimentation to demonstrate value across the business
• Contributing new ideas towards improving our current solutions, processes and unsolved business problems
• Working with the latest data science & AI technologies, and continuously learning and adapting in this fast-evolving space
• Being pro-active and staying up to date with latest trends in analytics and technology

PERSONAL PROFILE

• Advanced degree, MSc or PhD in a quantitative field (e.g., Data Science, Mathematics, Statistics, Econometrics, Computer Science, Physics, Engineering etc)
• Some experience as a Data Scientist in a commercial environment and customer focused business or demonstrated experience with data science and statistical techniques.
• Solid foundation in programming and experienced in Python.
• Hands-on experience in one or more of the following is preferred: time series, recommendation systems, customer journey modelling techniques, deep learning or large language models (LLMs)
• Strong in problem-solving, combining both a logical and innovative approach
• Good, in-depth, understanding of data science concepts and hands-on practical use of mathe-matical, statistical, machine learning and deep learning techniques
• Strong desire and proven ability to continuously learn new software, technologies and methodologies and keep up with latest data science trends & AI models
• Collaborative approach to work, working in teams towards delivering a business objective.
• Self-starter, proactively identifying opportunities where analytics can add value and translating business requirements in analytical framework
• Excellent communication skills with the ability to explain complex analytics to stakeholders