Lead Data Scientist

Description

The company wants a generalist data scientist to lead machine learning across Membership, Food & Beverage, Operations, Digital and Events.

In this role you become the main expert for building predictive and prescriptive tools from large datasets, covering member churn, personalised content, and demand forecasts that help the venues staff correctly.

You take models from concept to production, then keep them accurate and useful, and keep looking for new ways to add value for members and the business.

You also help the wider analytics team measure impact better, so business decisions rely on solid evidence.

Responsibilities

• Own the design, build and ongoing improvement of the machine learning portfolio: member churn and segmentation, personalisation and recommendation engines (for example for events), and demand forecasting for labour and operations planning.
• Work with stakeholders to define problems, choose the best approach even when it is not machine learning, and set success measures linked to commercial results.
• Manage the full model lifecycle: scoping, development, validation, deployment, monitoring, scheduled recalibration and retirement.
• Set up ML Ops standards covering version control, a model registry, documentation and governance.
• Work with Data Engineering to deploy models on GCP, Snowflake and Airflow, with dependable scoring pipelines whose outputs other tools and teams can use.
• Build monitoring for model accuracy against agreed thresholds and baselines, for data drift, and for business impact, with clear alerts and regular reviews.
• Set the standard for advanced measurement across the analytics team, teaching analysts and advising them on experimentation and causal inference, and choosing practical, sound alternatives when randomisation is not possible.
• Build reusable frameworks, templates and guidance so analysts can run sound tests and impact studies independently.
• Coach analysts and build their skills to support wider data literacy across the business.
• Work with Membership, Marketing/CRM, Digital, Operations and Finance to rank data science work by value.
• Explain complex methods and uncertainty in plain language to non-technical audiences, including senior leaders.
• Direct and check the work of offshore data science resources when the workload requires it: scope tasks, review code and models, and keep standards consistent.

Requirements

• Essential: at least 5+ years of hands-on data science experience, typically, across varied problem types such as classification and propensity, recommendation, time-series forecasting, and clustering and segmentation.
• Essential: a record of deploying models and maintaining them after launch, not only building prototypes.
• Essential: strong Python skills, which is the company's preferred language, along with its data science libraries.
• Essential: solid grounding in statistics, experimentation and causal inference, including A/B testing, power analysis, variance reduction, difference-in-differences, synthetic control or similar methods.
• Essential: strong stakeholder skills, turning vague business questions into clear problems and explaining results in plain English.
• Essential: able to work as a senior hands-on individual contributor who sets direction and reviews others' work without managing them directly.
• Desirable: experience with a modern cloud data stack, ideally Snowflake (Snowpark, Cortex) and dbt.
• Desirable: practical ML Ops experience, for example MLflow or similar, Git, CI/CD, containerisation, and automated retraining and monitoring.
• Desirable: experience using LLM and GenAI tools in your own development workflow and for data enrichment, such as classifying text or extracting structure from unstructured text.
• Desirable: experience in hospitality, membership, subscription, retail or consumer businesses.
• Desirable: experience coaching analysts or building a culture of measurement and experimentation.

Benefits

• Competitive pay and global benefits and perks.
• Training to build technical and management skills, whether you are early in your career or moving up.
• Discounts at the company's venues worldwide and at its other brands.
• Annual membership to every House.
• Enhanced pension scheme.
• Private health and dental care.
• Cycle to work scheme or season ticket loan.
• 3 days of paid leave a year to support a charity of your choice, arranged with the company's impact team.
• Access to food and drink training programmes, events and learning opportunities.
• Monthly social events such as fitness sessions, cinema screenings and art classes, which you can sign up for.