Director of Data and AI

About the role

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 communicate effectively with senior stakeholders and non-technical audiences
Commercial awareness with experience managing budgets, prioritising investment, and optimising data and AI costs
A pragmatic, delivery-focused mindset with the ability to balance short-term business needs and long-term Data and AI strategy