Lead Data Scientist

Responsibilities

• Lead the design, optimization, and evolution of yield, pricing, and matching models to improve forecasting accuracy and stability.
• Analyze large-scale historical trading and behavioral datasets to uncover patterns, risks, and performance opportunities.
• Define data science strategy for yield optimization, balancing innovation with robustness in live production environments.
• Partner with commercial, engineering, and product leaders to embed data-driven decisioning into operational workflows.
• Guide and mentor senior and mid-level data scientists, setting high standards for analytical quality and delivery.
• Communicate complex technical findings clearly to non-technical audiences to enable actionable business decisions.

Requirements

• Advanced expertise in data science and statistical modeling.
• Strong proficiency in Python or R and applied optimization techniques.
• Demonstrated experience leading yield, pricing, or optimization use cases within large-scale marketplaces.
• Strong understanding of forecasting, optimization, and decision science in discrete choice or trading contexts.
• Experience working with cloud-based data platforms and scalable analytics environments (e.g., AWS, Azure, Redshift).

Benefits

• 25 days annual leave (increasing with tenure).
• Health cash plan and life assurance.
• Income protection.
• Enhanced employer pension contribution.
• Award-winning voluntary flexible benefits covering lifestyle, health, wealth, and wellbeing.

About the Company

Kantar is the world’s leading AI-native marketing data and analytics business and an indispensable brand partner to the world’s top companies. By combining deep human understanding with advanced data science and AI, we help brands grow and make confident decisions in a rapidly changing world.