Lead Data Scientist

Responsibilities

• Frame business problems with stakeholders, pick the right approach (which may not always be ML), and set clear success metrics tied to commercial outcomes
• Own the full model lifecycle: scoping, development, validation, deployment, monitoring, scheduled recalibration and retirement

ML Ops and production

• Work with Data Engineering to put models into production on our stack (GCP, Snowflake, Airflow), with reliable scoring pipelines and outputs that downstream tools and teams can use
• Build monitoring and observability for model accuracy in production (tracked against agreed thresholds and baselines), data drift and business impact, with clear alerts and review cycles
• Create reusable frameworks, templates and guidance so analysts can run sound tests and impact measurement on their own
• Direct and quality-assure work from offshore data science resources when workload requires: scope tasks, review code and models, and keep standards consistent

Requirements

• Excellent stakeholder skills: can turn a vague business question into a well-framed problem and explain results in plain English

Preferred

• Experience with a modern cloud data stack, ideally Snowflake (Snowpark, Cortex) and dbt
• Practical ML Ops experience, e.g. MLflow or similar, Git, CI/CD, containerisation, automated retraining and monitoring
• Experience with LLM and GenAI tools, both for your own development workflow and for data enrichment (e.g. classifying or extracting structure from unstructured text)
• Experience in hospitality, membership, subscription, retail or consumer businesses
• Experience coaching analysts or building a measurement or experimentation culture

Essential

Significant hands-on data science experience (typically 5+ years) across a broad range of problem types, such as classification and propensity, recommendation, time-series forecasting, clustering and segmentation

A track record of putting models into production and owning them afterwards, not just building prototypes

Strong Python (our preferred language) and its data science ecosystem

A deep grounding in statistics, experimentation and causal inference (A/B testing, power analysis, variance reduction, difference-in-differences, synthetic control or similar)

Comfortable as a senior hands-on IC who can also set direction for others and review their work without line-managing them

Desirable

Benefits..

Soho House offers competitive compensation packages that feature global benefits and perks. Whether you’re seeking entry-level employment or a new opportunity to expand your profession, we offer training to develop the technical and managerial skills necessary to grow your career.

Discounts at Soho House globally, as well as Soho Home and Cowshed

Annual Every House Membership

Enhanced Pension Scheme

Private Health and Dental Care

Cycle to Work Scheme/Season Ticket Loan

• In conjunction with Soho Impact, take 3 days paid a year to support a charity of your choice.
• Cookhouse & House Tonic: Our Cookhouse & House Tonic programmes offer unique food and drink trainings, events and opportunities to inspire and educate.
• Team Events: From fitness sessions to cinema screenings and art classes, each month we hold a series of fun events which you can sign up to.