Head of ML Data Science [Search, Recommendation, Ranking, Personalisation] (Seattle)

About the Role

We are seeking a Head of Data Science to lead and scale our Data Science team. This is a senior leadership role at the intersection of cutting-edge AI innovation and high-impact production systems.

You will be managing a central team including managers, Data Scientists, ML and software engineers) across multiple pillars, including Personalisation & Search, Recommendation, AI optimisation, GenAI and ML platform.

Key Responsibilities

• Develop data-driven business insights and work with cross-functional stakeholders to identify opportunities and recommend prioritisation of product, growth and optimisation initiatives
• Lead, mentor, and grow a high-performing team of data scientists focused on algorithm development, machine learning, experimentation and advanced analytics.
• Partner with Product, Engineering, and Design to integrate solutions into scalable, production-grade systems and customer-facing experiences
• Champion data-driven decision-making, ensuring that product and strategy decisions are informed by rigorous quantitative analysis.
• Drive innovation by staying current with emerging research, technologies, and industry best practices in algorithms, optimisation, and applied machine learning.

Qualifications

• 10+ years of progressive experience in data science, machine learning, optimisation, or causal inference, including building and deploying algorithms in production systems
• 3+ years of people management experience leading high-performing technical teams, with a proven ability to mentor, develop, and retain top talent.
• Deep expertise in machine learning, experimental design, causal inference, and statistical methodologies, with a track record of applying them to high-stakes product or marketplace decisions.
• Experience in algorithm development and prototyping, and with productionizing algorithms for real-time systems.
• Experience navigating complex, ambiguous problem spaces and guiding teams through prioritisation, tradeoffs, and execution.
• Strong communication and influence skills, with the ability to engage both technical and executive stakeholders, align priorities, and build consensus.
• Strong analytical skills, with experience in extracting user behaviour insights from large datasets.