Burberry Data Scientist
- Employment
- Full-Time
- Seniority
- Entry-Level
- Department
- IT & Technology Systems
- Industry
- Fashion, Apparel & Leather Goods
- Posted
- Oct 2, 2026
About Burberry
Burberry Limited, a quintessentially British luxury fashion house, is renowned for its innovative designs and commitment to quality. As part of the global luxury conglomerate, Burberry offers a dynamic and inclusive work environment where creativity and excellence are at the forefront. The company is dedicated to fostering a culture that encourages diversity and sustainability, making it a leader in the luxury industry.
Burberry is seeking an early-career Data Scientist for its Customer Data Science team in London to develop customer models, recommendations and scalable analytics solutions that inform personalised experiences and business decisions. The role suits candidates with master’s-level knowledge or approximately one year of relevant experience and involves collaboration with data scientists, engineers and business stakeholders.
Role & Responsibilities
- Develop statistical models, machine learning solutions and data-driven tools to support customer and business objectives.
- Explore and prepare data sources, assess data quality, and create features for modelling and analysis.
- Apply propensity modelling, causal inference and experimentation to understand customer behaviour and measure customer outreach impact.
- Contribute to product recommendation, discovery and client relationship solutions that improve customer relevance.
- Collaborate with data scientists and engineers to build scalable, reliable, production-ready solutions.
- Monitor and evaluate production models using technical and business measures, identifying opportunities for improvement.
- Optimise existing models and analytics solutions through structured test-and-learn approaches.
- Translate business questions into analytical frameworks, methodologies and practical solutions.
- Generate reliable insights and recommendations for strategic and operational decisions.
- Present analytical methods, findings and limitations to technical and non-technical stakeholders.
- Identify opportunities to improve models, processes and team practices.
- Explore data science and AI developments, applying new technologies where they can deliver meaningful value.
Qualifications
- A master’s degree or PhD in a quantitative discipline such as Data Science, Mathematics, Statistics, Econometrics, Computer Science, Physics or Engineering, or equivalent technical knowledge.
- Master’s-level project, placement or internship experience, or approximately one year of relevant experience in data science or a closely related role.
- Experience applying statistical analysis, machine learning or data science techniques to practical problems in an academic or commercial setting.
- Sound understanding of mathematics, statistics, experimental design and model evaluation.
- Practical experience developing, testing and interpreting statistical or machine learning models.
- Exposure to one or more specialist areas, such as time series, recommendation systems, customer journey modelling, causal inference, deep learning or large language models.
- Practical programming experience using Python and SQL.
- Familiarity with libraries and technologies such as Pandas or PySpark is advantageous.
- Understanding of collaborative development practices, including version control tools such as Git.
- Exposure to Python packaging tools such as Poetry is welcomed but not essential.
- Logical, considered problem-solving and curiosity about new analytical methods.
- Ability to translate business requirements into structured analytical questions and practical approaches.
- Collaborative working style and ability to contribute effectively across technical and business teams.
- Clear communication skills and ability to explain complex analysis to different audiences.
- Commitment to learning and keeping informed about developments in data science, machine learning and AI.
Skills
Experience
Master’s-level project, placement or internship experience, or approximately one year of relevant experience in data science or a closely related role.
Education
A master’s degree or PhD in a quantitative discipline such as Data Science, Mathematics, Statistics, Econometrics, Computer Science, Physics or Engineering, or equivalent technical knowledge.
Workplace
The successful candidate will be located in London, England, UK.
Culture
Burberry fosters a creative and inclusive workplace culture that values diversity and sustainability. The company is committed to being a force for good, driving industry change and championing community engagement.
About Cerulean
Cerulean is the definitive career portal for the global luxury industry. We match exceptional professionals with exclusive opportunities at the world's most prestigious brands. From haute couture and fine watchmaking to prestige beauty, hospitality, and boutique retail, Cerulean centralises luxury employment to help you find the career for which you were destined.
Frequently Asked Questions
The luxury industry is characterised by a diverse and nuanced nomenclature. Esteemed houses frequently employ proprietary terminology, and even within a single organisation like Burberry, titles may vary across global markets to reflect local conventions. To ensure absolute clarity, Cerulean assigns a standardised, industry-coherent canonical title to every listing. However, it is worth noting that this role is functionally synonymous with «Machine Learning Scientist», «Applied Data Scientist», «Data Science Analyst», «Customer Analytics Scientist», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.