Head of Data Science

About the role

Paddle is building a data science capability from the ground up to turn its unique payment and subscription data into economic value. As Head of Data Science you will own automated decisioning inside the product, delivering machine‑learning and agentic systems that drive revenue, growth and risk management.

Key responsibilities

• Prioritise high‑impact use‑cases across payment performance, revenue recovery, growth, and compliance, building a value‑based backlog and sequencing work with product, risk and finance stakeholders.
• Design, develop, and launch the first end‑to‑end system – from data analysis and feature engineering to model training, deployment, and A/B testing.
• Operate live decisioning systems, handling monitoring, drift detection, incident response and roll‑backs.
• Define and implement the production stack with reproducible training data, model registry, inference services, feature stores and observability tooling.
• Hire, mentor and lead a hub‑and‑spoke team of senior data scientists and ML engineers, setting standards and reusable components.
• Establish governance for automated decisioning, working with legal, privacy, compliance and risk on GDPR, EU AI Act and payments regulations.

Required profile

• Proven experience leading data‑science or ML teams that own production systems delivering measurable commercial impact.
• Hands‑on ability to write SQL and Python, engineer features, train models and bring them to production in the first months.
• Deep knowledge of both traditional ML (propensity, uplift) and agentic systems (prompt engineering, evaluation against golden answers).
• Track record of operating live ML systems – monitoring, retraining, incident handling and on‑call responsibility.
• Experience in payments, fintech or other regulated transactional domains is strongly preferred.

Required skills

• SQL
• Python
• Machine learning
• Agentic systems
• Model registry and inference services
• Feature stores and drift detection
• Trace observability