Director of Data and AI

Director of Data and AI

Department: Platform

Employment Type: Permanent

Location: London

Reporting To: James Complin

We’re seeking a strategic Director of Data and AI to lead, develop, and empower our Data and AI teams. This role balances leadership with technical excellence; you’ll define how data, analytics, machine learning, and generative AI enable the wider business.

You’ll work closely with senior stakeholders, translating business objectives into a clear Data and AI strategy, and ensuring the team delivers scalable, trusted, secure, and commercially impactful solutions. The ultimate goal will be to establish Data and AI as a strategic capability that supports better decision‑making, improves customer and partner outcomes, and unlocks new opportunities across the business.

• Lead, manage, and develop the Data and AI team, driving a culture of accountability, collaboration, innovation, and continuous improvement
• Define and execute the Data and AI strategy in alignment with wider business goals
• Partner with senior stakeholders across Engineering, Product, Risk, Commercial, Finance, and the wider business to ensure Data and AI capabilities enable delivery, growth, and operational excellence
• Ensure the business has access to accurate, timely, and actionable data, enabling self‑serve analytics and insight‑led decision‑making
• Own and improve the reliability, scalability, governance, quality, security, and performance of data and AI platforms, products, and services
• Establish clear metrics to measure the impact of Data and AI initiatives, data quality, model performance, adoption, and team effectiveness
• Drive best practices across data engineering, analytics, machine learning, data governance, experimentation, model monitoring, and responsible AI
• Ensure that AI solutions are robust, explainable, compliant, and aligned to business outcomes
• Support career development, mentoring, and succession planning within the team
• Contribute to wider technology and business leadership discussions, helping shape how data and AI are used responsibly and effectively across the organisation

• Proven experience leading Data, Analytics, Machine Learning, or AI teams at a senior level; ideally within a fintech environment
• Strong people leadership skills, with a track record of building and developing high‑performing, multi‑disciplinary teams
• Experience defining and delivering Data and AI strategy aligned to business outcomes
• Deep understanding of modern data platforms, data architecture, data modelling, data pipelines, analytics engineering, machine learning systems, and AI‑enabled products
• Strong knowledge of data governance, data quality, privacy, security, regulatory considerations, and responsible AI principles
• Experience delivering production‑grade data and AI solutions, including model deployment, monitoring, evaluation, and lifecycle management
• Strong hands‑on understanding of modern data and AI tooling, ideally including SQL, Python, Snowflake, dbt, Airflow, Metabase, Tableau, and AWS‑based data services
• Experience with data ingestion, streaming, and change data capture tooling, such as Fivetran, Estuary, or similar platforms
• Experience working with cloud data warehouses and operational databases, particularly Snowflake and Postgres
• Familiarity with BI and self‑serve analytics platforms such as Metabase and Tableau, with an understanding of how to drive adoption across business teams
• Experience with SQL transformation and analytics engineering workflows using dbt, including governance, standards, and enablement for analytics engineers
• Ability to oversee API‑based and batch data extraction processes, particularly those built in Python and orchestrated using Airflow
• Understanding of machine learning tooling and lifecycle management, ideally including DVC, MLflow, Evidently AI, or equivalent platforms for experiment tracking, versioning, monitoring, and evaluation
• Ability to work effectively across a data ecosystem that uses a range of AWS services to support ingestion, orchestration, transformation, machine learning, monitoring, and platform operations
• Ability to influence and…