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

Burberry is making a major investment in expanding our data and analytics capability. Over the last few years, we have created a global omni-channel single customer view, built an outstanding and modern analytics platform, and developed a highly effective analytics and data science team. We’re now building on these foundations to drive and embed data-inspired decision making across Burberry.

We are recruiting Data Scientists to join our fast-expanding data science team and contribute to our core strategic focus areas across:

As a Data Scientist, you will be accountable for researching, 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.

Are you a data scientist, or a recent graduate with an advanced degree in a quantitative field, and with a proven record of using data, statistical modelling, machine learning or 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 data 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 strategy
• Presenting the analytics solutions, models and insights to a range of business stakeholders and contributing to strategic decisions
• Contributing new ideas towards improving our current solutions, processes and unsolved business problems, having the opportunity to directly feed into our data strategy agenda and roadmap
• Working within cross-functional teams and delivering under an agile project-based framework
• Working with the latest big data 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 is an advantage
• Interest and hands-on experience with time series, deep learning, recommendation systems, classification, clustering and regression techniques, is preferred
• Proven personal portfolio of projects where analytics and data science were used to drive business value and decisions
• Strong in problem-solving, combining both a logical and innovative approach
• Good, in-depth, understanding and extensive practical use of mathematical, statistical, machine learning and deep learning techniques
• Solid foundation in programming and proficient in Python. Additional experience with deep learning frameworks, such as PyTorch or Tensorflow would be beneficial
• Understanding and interest in big data technologies (Spark, Hadoop, etc)
• Strong desire and proven ability to continuously learn new software, technologies and methodologies and keep up with the fast-evolving field of big data
• Collaborative approach to work, working in teams towards delivering a business objective
• Strong time management skills and ability to plan and prioritise over multiple requests
• 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