AI Lead Data Scientist - BPL

What you'll do as the AI Lead Data Scientist Director for BPL:

Provide strategic leadership and responsibility for AI / ML‑driven decisioning across the Payments domain.

Be responsible for supporting teams in translating complex business problems into explainable, regulated, and commercially impactful decision systems, ensuring that advanced analytics and AI are applied in a manner consistent with Model Risk Management (MRM), AI governance, and regulatory expectations.

Scope & Complexity

• Operates at enterprise Payments domain level, influencing multiple product lines and decision processes

• Responsible for end‑to‑end model development lifecycle, from problem framing to production monitoring

• Influences senior stakeholders across Payments leadership, Risk, Compliance, Product, and Engineering

Key Accountabilities

• AI / ML Development - responsibility for AI / ML‑driven decisioning and model development practice across the Payments domain, ensuring models support delivery, merchant acquisition, pricing, fraud, risk, and customer experience outcomes

• Modelling Standards & Strategy -Definition and enforcement of modelling standards, experimentation frameworks, and analytical best practices across Payments use cases

• Senior Stakeholder Advisory - Acting as a senior advisor to Payments leadership and control functions on AI‑driven decisioning strategy and risk trade‑offs

• Capability & Culture - Building sustainable data science capability and embedding a culture of responsible, outcome‑driven AI

Key Responsibilities

• Payments‑Focused Problem Framing & Strategy

• Support the definition of AI / ML strategies for core Payments use cases, including delivery, merchant acquisition, pricing optimisation, fraud detection, and transactional analytics

• Translate business objectives into structured modelling, experimentation, and decision frameworks

• Define KPIs aligned to commercial and risk outcomes, not just predictive accuracy

• Advanced AI, Modelling & Decision Intelligence

• Lead development of advanced models and advanced analytical techniques (e.g. GenAI, propensity, LTV, fraud, pricing optimisation)

• Ensure models are robust, explainable, and production‑ready

• Establish closed‑loop learning systems where decisions are continuously monitored and improved

• Generative AI & Agentic Analytics

• Apply generative AI and LLMs to analytics workflows, insight generation, and feature discovery

• Design and validate AI agents supporting Payments decisioning and analytics processes

• Partner with AI Engineering and AI Ops to deploy governed production solutions

• Model Risk, Validation & Governance

• Define validation, monitoring, and drift detection standards

• Ensure AI governance, fairness, and explainability requirements

• Produce audit‑ready documentation and evidence

• Data & Feature Strategy

• Support the definition of the AI/ML the data strategy and it’s implementation working with other engineering teams.

• Promote reuse of shared AI/ML assets

Essential Skills/Experience (Job Architecture)

• Advanced quantitative expertise (Statistics, Mathematics, Computer Science, Economics or equivalent)

• Deep knowledge of machine learning, statistical modelling, experimentation, and causal inference

• Strong Python and modern data science tooling capability

• Proven experience delivering AI / ML models into production within regulated environments

• Strong understanding of model validation, monitoring, and governance

• Ability to influence senior commercial and risk decision‑makers

Desirable Knowledge & Experience

• Experience in Payments, merchant acquiring, fintech, or financial crime

• Experience with large‑scale transactional datasets

• Familiarity with cloud‑based AI platforms and agent frameworks

• Experience with generative AI and agentic analytics

• PhD or equivalent advanced research experience

Risk and Control:

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.

About BPL:

Barclays’ payments acceptance business provides critical infrastructure to the UK economy, processing billions of pounds of payments annually for both small businesses and domestic and international corporate clients.

In April 2025, we announced a long-term partnership with Brookfield Asset Management to grow and transform the payments acceptance business by broadening the range of services offered, enhancing the experience for both existing and prospective clients. Leveraging extensive client relationships and deep experience of UK payments, we will create an environment of continuous innovation - activated by Brookfield’s global private equity expertise in payments, technology, operational transformation and corporate carve-outs - to ensure the business is strategically positioned for long-term growth.

Barclays will invest approximately £400m in the new business, the majority of which will be incurred during the first three years. Performance-linked incentives will drive greater alignment between the partners, underpinning the long-term commitment to the transformation. Barclays and Brookfield will work to create a standalone entity over time, continuing to use the Barclaycard Payments (BPL) brand and acting as the sole payments acceptance services provider to Barclays’ clients for a minimum of ten years. 

For more information on our partnership with Brookfield, please visit Barclays.com.

To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation. 

Accountabilities

• Identification, collection, extraction of data from various sources, including internal and external sources.
• Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
• Development and maintenance of efficient data pipelines for automated data acquisition and processing.
• Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
• Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.

Director Expectations

• To manage a business function, providing significant input to function wide strategic initiatives. Contribute to and influence policy and procedures for the function and plan, manage and consult on multiple complex and critical strategic projects, which may be business wide..
• They manage the direction of a large team or sub-function, leading other people managers and embedding a performance culture aligned to the values of the business. Or for an individual contributor, they lead organisation wide projects and act as deep technical expert and thought leader, identifying new ways of working and collaborating cross functionally. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions..
• Provide expert advice to senior functional management and committees to influence decisions made outside of own function, offering significant input to function wide strategic initiatives.
• Manage, coordinate and enable resourcing, budgeting and policy creation for a significant sub-function.
• Escalates breaches of policies / procedure appropriately.
• Foster and guide compliance, ensure regulations are observed that relevant processes in place to facilitate adherence.
• Focus on the external environment, regulators, or advocacy groups to both monitor and influence on behalf of Barclays, when appropriate.
• Demonstrate extensive knowledge of how the function integrates with the business division / Group to achieve the overall business objectives.
• Maintain broad and comprehensive knowledge of industry theories and practices within own discipline alongside up-to-date relevant sector / functional knowledge, and insight into external market developments / initiatives.
• Use interpretative thinking and advanced analytical skills to solve problems and design solutions in often complex/ sensitive situations.
• Exercise management authority to make significant decisions and certain strategic decisions or recommendations within own area.
• Negotiate with and influence stakeholders at a senior level both internally and externally.
• Act as principal contact point for key clients and counterparts in other functions/ businesses divisions.
• Mandated as a spokesperson for the function and business division.

All Senior Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.