Head of Data Science (AI)

TL;DR

Head of Data Science (ML/AI): Building a core data science function to unlock value across a global beauty and wellness marketplace with an accent on transitioning from reactive to proactive ML delivery. Focus on establishing experimentation disciplines, scaling the DS team, and shipping high-impact ML products that drive measurable business outcomes.

Location: On-site in London (5 days per week)

Salary: £95,000 - £110,000 per year

Company

AI-powered operating system for the global beauty, wellness and self-care industry.

What you will do

• Define the DS roadmap and align it with business priorities across marketplace, payments, and partner growth.
• Transition the DS function from reactive request fulfillment to proactive opportunity identification and POC development.
• Ship production ML products that drive measurable business impact and outcomes.
• Establish experimentation as a discipline, including A/B testing infrastructure and causal inference.
• Build foundational DS infrastructure such as feature stores, model governance, and CI/CD for ML.
• Scale and develop the DS team across ML engineering, data science, and MLOps.

Requirements

• 4-5 years of experience in data science or ML engineering.
• 3+ years of experience directly managing and growing data science teams.
• Proven track record of building a DS function from the ground up at a scaling company.
• Experience shipping production ML models at scale with real business outcomes.
• Strong stakeholder management skills for influencing C-suite and product leaders.
• Must be based in London and available to work on-site 5 days per week.

Nice to have

• Experience in marketplace, SaaS, or fintech industries.
• Familiarity with SageMaker, Snowflake, dbt, and Docker.
• Experience building MLOps or experimentation platforms.
• History of thought leadership via blog posts or conference talks.

Culture & Benefits

• Work with real-world scale involving millions of transactions across 120+ countries.
• Access to a strong existing technical foundation and production ML stack.
• High visibility and direct impact on business metrics.
• Inclusive workforce culture prioritizing diversity and empowerment.
• Dog-friendly office environment.

Hiring process

• Screening video call with the Talent Team.
• Technical and soft skills interview via Google Hangout.
• In-person case study and live review with the team.
• Final stakeholder interview with the Deputy CPO or CTO.