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. This partnership marks a bold new era for Lyst, as we accelerate our vision and work together to transform the future of fashion shopping through AI and technology.
At Lyst, we obsess over the customer, providing a search & discovery experience which offers inspiration, fulfilment, and personalisation. We believe that fashion is amazing but shopping for fashion often isn't, and use our technology, data and creativity to bring more joy, greater choice and fewer fails. 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 be working 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.
Responsibilities
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
Requirements
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
Benefits
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 want you to enjoy using the Lyst app and site as much as our customers, so we provide you with a clothing allowance to use on Lyst every year. This starts at £250 when you join and increases up to £1,000 with your length of service.
Private Healthcare:Our healthcare provider is Vitality. Your health is important to us which is why we offer all employees a comprehensive healthcare scheme from the day you start.
Training Allowance:We’re big on continuous learning and growth, so all employees are currently entitled to an annual training allowance of £1,000. This can be used to attend conferences, industry events, training courses and to purchase resources.
Pension Scheme:Our pension provider is The People’s Pension. We offer a minimum employee contribution of 5% and 3% employer contribution.
Eye Tests and Vouchers:Employees can make a saving on their eye test and glasses through our chosen provider. You’ll receive a free eye test every year and a discount towards glasses.
Cycle-to-Work Scheme:Lyst will purchase a bicycle from your chosen retailer, you will then receive a voucher to pick up your bicycle from them.
Transport Season Ticket Loan:Employees can apply for an interest free season ticket loan to support your travel to work.
Social Events:Frequent company wide social events including Christmas & summer parties, themed events, as well as smaller team socials. We also have plenty of interest based groups such as football, running club, book club, culinary and more.
