Define and own the enterprise data science strategy and roadmap.
Collaborate with senior stakeholders across product, technology, and commercial teams to align data science with strategic priorities.
Build and lead a high-performing data science team focused on innovation, rigor, and measurable outcomes.
Champion a culture of experimentation, causal inference, and evidence-based decision-making (A/B testing, uplift modelling).
Deliver robust machine learning and analytics solutions across domains like customer personalisation, predictive forecasting, fraud detection, customer lifetime value and churn prediction.
Partner closely with Data Engineering and Platform teams to ensure seamless delivery, high-quality pipelines, and scalable deployments.
Embed best practices in data ethics, privacy, and regulatory compliance.
Requirements
Proven success leading large-scale data science initiatives in a commercial setting.
Expertise in applied machine learning, predictive modelling, experimentation, and statistical analysis.
Demonstrated ability to deploy and maintain production-grade models at scale.
Experience managing and developing high-performing teams in fast-paced environments.
Strong communication and stakeholder engagement skills — comfortable presenting to C-level audiences.
Hands-on proficiency with modern data science tools, languages (e.g. Python, SQL), and cloud platforms.
Familiarity with data contracts, feature stores, and real-time/streaming analytics (desirable).
Understanding of lakehouse architectures and modern data platforms (desirable).
Experience enabling AI-driven product capabilities or personalisation strategies (desirable).
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