Head of AI and Analytics Strategy and Exploration in London

About Us

We’re the world’s leading provider of secure financial messaging services, headquartered in Belgium. We are the way the world moves value – across borders, through cities and overseas. No other organisation can address the scale, precision, pace and trust that this demands, and we’re proud to support the global economy. We’re unique too. We were established to find a better way for the global financial community to move value – a reliable, safe and secure approach that the community can trust, completely. We’re always striving to be better and are constantly evolving in an ever‑changing landscape, without undermining that trust. Five decades on, our vibrant community reflects the complexity and diversity of the financial ecosystem. We innovate diligently, test exhaustively, then implement fast. In a connected and exciting era, our mission has never been more relevant. Swift now has a presence in 200+ countries and legal territories to serve a community of more than 12,000 banks and financial institutions.

Role Purpose

To shape, inspire, and prepare Swift for the age of AI… defining what is possible, building the case for where to act, and ensuring the organization has the vision, appetite, and capability to lead. By leveraging existing AI and Analytics capabilities, you pioneer how they can deliver tangible business value and set Swift up for success in the coming years.

Responsibilities

• Strategic foresight – monitor the evolution of AI and Analytics technologies, market dynamics, and ecosystem players, translating external signals into clear and actionable business strategic implications for the organization. Build forward‑looking perspectives on how AI will reshape the industry, our customers, and our operating models. Provide structured, fact‑based guidance to senior leadership on what matters now and what will matter next.
• Communicate the art of the possible – champion AI’s potential across the organization, translating cutting‑edge capability into compelling narratives that inspire curiosity and ambition, building shared understanding of what AI can deliver today and shaping a credible, forward‑looking vision for where it is headed.
• Opportunity exploration – identify and pursue high‑value opportunities at the intersection of enterprise priorities and AI and Analytics capability, challenge existing assumptions, surface non‑obvious use cases, and build the case for bold bets. Drive momentum from insight to action, ensuring promising opportunities are translated into tangible initiatives rather than remaining theoretical.
• Experimentation and delivery – drive AI and Analytics opportunities end to end, from early hypothesis through experimentation, proof‑of‑concept, and into validated outcomes. Maintain momentum across the full arc, ensuring promising ideas don’t stall at the exploratory stage, communicate progress, learnings, and results in a way that builds organizational confidence and appetite for further investment.
• Portfolio construction & prioritization – build and maintain a balanced AI and Analytics portfolio that combines near‑term impact with longer‑term strategic bets. Recommend investment priorities and sequencing, ensuring alignment with enterprise strategy and risk appetite. Enable informed, fact‑based decision‑making at executive level through clear framing of trade‑offs, value, and dependencies.
• Leadership & team development – lead, coach, and develop a team, setting clear objectives and high standards for delivery, ensuring accountability for quality, performance, and outcomes while fostering a culture of curiosity, rigor, and continuous learning.
• External relationships and partnerships – own and cultivate relationships with key external stakeholders including customers, technology vendors, research institutions, and ecosystem partners. Identify and drive partnership opportunities that accelerate Swift’s AI and Analytics agenda, bringing in capability, insight, and influence that would be difficult to build internally.
• External representation and thought leadership – represent Swift externally as a credible voice on AI and Analytics strategy, articulating a compelling and coherent narrative about where Swift is headed and why it matters. Contribute to industry forums, client conversations, and public discourse in a manner that builds Swift’s reputation as a forward‑thinking leader in the application of AI across financial market infrastructure.

Qualifications & Experience Required

The ideal candidate brings a strong track record in strategy and exploration, with 5–10 years of relevant experience and a solid commercial grounding in AI and Analytics within the financial services industry. They combine disciplined execution with strategic vision, and demonstrate curiosity, foresight, and a genuine passion for applying emerging technologies to complex, real‑world challenges at global scale. Beyond experience, the role requires the ability to navigate ambiguity, shape direction, and translate innovation into meaningful outcomes for Swift and its community.

Experience and Background

• 10+ years in data, analytics, or AI roles, with at least 3–5 years at a senior or leadership level.
• Demonstrated experience setting AI or analytics strategy in a complex, enterprise environment, shaping direction and building the case for investment, not just delivering projects.
• Track record of translating technical capability into business outcomes including revenue growth, operational efficiency, and risk reduction.
• Comfortable operating in a matrixed organization, influencing without direct authority across product, engineering, commercial, and senior leadership teams.

Technical Fluency

Sufficient depth to interrogate technical proposals, assess feasibility, and hold vendors and partners accountable. Working knowledge of modern AI and ML approaches including classical ML, large language models, and agentic systems, with sound judgment on when each is appropriate. Understanding of data infrastructure fundamentals – pipelines, governance, and data quality – as a prerequisite to realizing AI value at scale.

Preferred Qualifications

• Deep familiarity with regulated AI deployment including governance frameworks, explainability requirements, and vendor risk management.
• Commercial exposure: having owned or influenced a P&L, shaped a product, or worked directly with enterprise clients on AI adoption.
• Hands‑on background in data science, ML, or software engineering earlier in career, lending credibility with technical teams and sharpening build‑versus‑buy instincts.
• Familiarity with agentic AI architectures, multi‑model orchestration, and emerging AI infrastructure patterns.
• Background in or alongside consulting, advisory, or product strategy functions.
• Strong external network across AI research, fintech, or financial standards bodies.
• Desirable: experience working in or closely with financial services, payments, or infrastructure‑adjacent sectors, with a strong understanding of industry dynamics, regulatory environments, and client expectations.
• Exposure to the SWIFT ecosystem or equivalent – correspondent banking, ISO20022, sanctions screening – would meaningfully accelerate onboarding.

What We Offer

We give you the freedom to be yourself. We are creating an environment of unique individuals – like you – with different perspectives on the financial industry and the world. A diverse and inclusive environment in which everyone’s voice counts and where you can reach your full potential. We are committed to an inclusive and accessible recruitment process. If you require a reasonable accommodation related to accessibility during your application or interview, please contact or indicate this in your application. All requests are confidential and will not affect your candidacy.