Senior Data Scientist

Lyst is a global fashion shopping platform founded in London in 2010 and catering to over 160M shoppers per year. We offer our customers the largest assortment of premium & luxury fashion products in one place, curating pieces from 27,000 of the world's leading brands and stores. In 2025, Lyst joined Zozo, operators of Zozotown, the leading fashion e-commerce platform in Japan, to accelerate our vision and transform the future of fashion shopping through AI and technology. At Lyst, we obsess over the customer, providing a search & discovery experience that offers inspiration, fulfilment, and personalisation. Our mission is to help fashion shoppers make better choices and help fashion partners find better audiences as the category-leading destination for every fashion shopper.

The Role We’re looking for an experienced and impact-driven Senior Data Scientist to join our Discovery team, focused on helping customers find products they love through better search, recommendations, and personalisation. This is a high-responsibility role that blends advanced modeling, analytical investigations and project ownership. You’ll take the lead on projects that improve the core discovery experience—such as personalisation, relevance ranking, and multi-modal retrieval—as well as conduct deep investigations into user behaviour and feature performance. You’ll work across the full research and experimentation lifecycle: from framing the problem and exploring the data, to prototyping models, running offline evaluations, and validating ideas through AB testing. You’ll also contribute to literature reviews and research spikes—for example, investigating how to apply new developments in vector search, embeddings, or LLMs to our discovery stack. This is a senior position, so you’ll be expected to run projects independently: shaping roadmaps, communicating findings with clarity, mentoring junior team members, and collaborating closely with engineers, PMs and analysts to deliver measurable user and business impact. We work primarily in Python and SQL, with tools like Scikit-learn, Tensorflow, PyTorch and Pandas. Our ML stack runs on AWS and Sagemaker. We value clean, documented, well-tested and reviewed code—and have the tooling and culture to support this.

• Lead data science projects that improve product discovery features like search, recommendations and browsing
• Research and prototype new approaches using structured data, text, image and multi-modal embeddings
• Design and run offline evaluations to assess model changes before launch
• Conduct statistical investigations into customer behaviour and funnel performance (e.g. search abandonment, filter usage, session patterns)
• Run literature reviews and research spikes on emerging techniques—e.g. LLM-assisted retrieval, hybrid recommenders, contrastive learning
• Collaborate with ML engineers to move promising prototypes into production
• Design and analyse AB tests to evaluate impact on discovery metrics (e.g. conversion, engagement, retention)
• Present complex results to non-technical stakeholders with clarity and strategic insight
• Mentor junior data scientists, delegate tasks where appropriate, and help set technical direction

• 5+ years of experience in applied data science, preferably in search, recommendations or user modelling
• Strong Python and SQL skills, with deep experience in data exploration, feature engineering and model evaluation
• Proven experience applying and comparing models for structured prediction, ranking, retrieval or recommendation
• Strong understanding of offline evaluation techniques and trade-offs in information retrieval and recommender systems
• Ability to communicate clearly across disciplines and seniority levels—including product, design and engineering
• Experience planning and delivering projects end-to-end, from problem definition to experimentation and rollout
• Familiarity with AB testing design and analysis in online product settings
• Bonus: experience working with embeddings (e.g. image, text, product), vector search, LLMs or hybrid models

• Our Ways of Working: We all come into the office on Tuesdays and Thursdays, with the option to work remotely or come into the office on the other days. We believe that in person collaboration and community spirit is important, which is why we spend some of our time in the office and some of our time at home.
• Time Off: In addition to the 8 statutory bank holidays, you will receive 29 holidays per year. Lyst's holiday year runs from 1 April to 31 March.
• Competitive Family Leave Package: This includes Enhanced Family Leave for those eligible, paid Time off for Dependents and Support for Fertility Treatment & Loss.
• Clothing Benefit: We provide a clothing allowance to use on Lyst every year, starting at £250 when you join and increasing up to £1,000 with length of service.
• Private Healthcare: Comprehensive healthcare scheme from day one.
• Training Allowance: Annual training allowance of £1,000 for conferences, courses and resources.
• Pension Scheme: The People's Pension with 5% employee and 3% employer contribution.
• Eye Tests and Vouchers: Free annual eye test and discount towards glasses.
• Cycle-to-Work Scheme: Bicycle purchase with voucher to collect.
• Transport Season Ticket Loan: Interest-free season ticket loan.
• Social Events: Frequent company-wide events and interest-based groups.