Head of AI & Data Science

Reporting to:Chief Technology Officer (CTO)

Location:Hybrid (Remote but with frequent travel to Moneyhub offices in London & Bristol and client sites within UK)

Team:5 (Data Scientists & ML Engineers), growing within a wider Engineering org of 50+

The Mission

Moneyhub is an industry leader in data enrichment and categorisation. Our foundation is built on high-integrity financial data and robust machine learning. We serve the largest financial institutions who trust us to process millions of their consumers’ transactions every day.

We’re embracing the transition to agentic engineering, arming our teams with the best AI coding tools, and evolving our SDLC to move at pace in an AI world. We’re producing more quality code than ever before, to help solve client problems faster, and deliver better outcomes for their consumers.

Your mission is to partner directly with the CTO and CPO to accelerate our evolution into the world’s premier Intelligent Financial Decisioning and Data Platform. As a key leader within a 50-person engineering organization, you will influence the technical direction of the entire business. You will lead the shift from "data insights" to Agentic AI, architecting systems that don't just show data, but reason, plan, and act upon it. You will ensure that AI is not a "bolt-on" feature, but a fundamental capability that enhances our engineering standards, our product value, and our commercial moat

What do we offer?

We have offices in London and Bristol together with access to co-working space. We offer the opportunity to work remotely (role, business and client dependent) with support for your home office set-up if required. We have regular all company away days and other company, client and team meetings, your attendance at which will be mandatory.

Whilst this will be a remote first role we ask that applicants are based within commutable distance to either London or Bristol for regular in person meetings with the team.

Benefits include:

5% company contribution towards your Pension from your very first day with us. 3% contribution from your self.
25 days of holiday (plus bank hols), rising to 30 days after two years;
Choose to take your entitlement to UK bank holidays at other times based on your own days of significance;
Private medical insurance, including cover for pre-existing conditions, plus dental and optical benefit;
3 Months Moneyhubber Family Pay when you become a new parent;
Permanent health insurance and life cover - much greater than the industry standard (death in service);
Employee assistance programme;
Professional development support, with dedicated allowance of time and money;
Life event leave;
Cycle to work scheme;
EV Car Scheme
£750 towards professional memberships
Remote working benefits, including work from almost anywhere, access to co-working spaces and support for your home office set-up
High spec laptop
Holiday purchase

Core Responsibilities

1. Business-Wide Strategic Influence (30%)

C-Suite Partnership: Act as the strategic partner to the CTO and CPO, defining the roadmap for the "Intelligent Platform" and ensuring the business is ahead of the AI curve.
Engineering Leadership: Influence the wider 50-person engineering team by setting the standards for how AI and ML services are integrated, scaled, and maintained across the stack.
Commercial Strategy: Engage directly with senior AI leaders at our customers to understand their requirements and position Moneyhub as their essential intelligent infrastructure.

2. Hybrid Technical Architecture (40%)

Agentic Systems & Orchestration: Lead the architectural direction for multi-agent workflows, RAG, and vector embeddings. You own the "how" of our agentic future.
Traditional ML Excellence: Ensure our core data enrichment—built on "classic" DS (classification, regression, etc.)—remains industry-leading and serves as the high-fidelity foundation for our AI agents.
Pragmatic Algorithmic Direction: Champion the "simplest-first" approach. You will steer the team to know exactly when a 10-stage agentic workflow is necessary and when an optimized logistic regression is the superior commercial choice.

3. Practice Leadership & R&D (30%)

Lead and Grow: Direct leadership of a specialized team of 5, fostering a culture of high-velocity delivery and scientific rigor.
Roadmap Ownership: Shape the R&D backlog, ensuring that research tasks are directly tied to product outcomes and business growth.
Technical Quality: Provide the high-level guidance that saves the team time and improves system quality, ensuring we build "production-ready" intelligence, not just lab experiments.

Success Profile: The First 9 Months

1. Deep Immersion (3 Months)

Has become deeply familiar with our tech stack, our data schemas, and the specific "problem space" of Open Banking and financial wellness.
Has established high-trust working relationships across the 50-person engineering team and the wider business.

2. Technical Authority (6 Months)

Has provided clear technical direction that has tangibly saved the team time or improved system quality (e.g., through better orchestration patterns or more efficient model selection).
Has successfully integrated into the Product/R&D lifecycle, actively shaping the backlog and prioritizing high-leverage AI tasks.

3. External & Strategic Impact (9 Months)

Has represented Moneyhub in direct consultations with senior AI leaders at our key customers, influencing their strategy and securing our position as their premier data partner.
Has delivered the first production-ready Agentic Workflow that uses traditional ML outputs to execute autonomous financial tasks.
The team is recognized as a high-velocity unit that solves business-wide problems using the most efficient tool possible.

Target Candidate Profile: "The Architect of Intelligence"

DNA & Characteristics

Cross-Functional Influencer: Able to speak the language of the C-Suite, the Customer, and the Engineer. You can translate a high-level business goal into a 10-stage agentic workflow.
The Pragmatic Visionary: You are "au fait" with the latest in RAG, Embeddings, and Orchestration, but you have the discipline to prefer a simple algorithm if it solves the problem more effectively.
Systemic Thinker: You don't just think about "the model"; you think about how that model interacts with a 50-person engineering ecosystem and a global customer base.

Technical "Must-Haves"

Full-Spectrum Expertise: Mastery of the modern AI stack (LLMs, Agentic frameworks, Vector DBs) combined with a deep respect for "Traditional" Data Science (Python, Scikit-learn, etc.).
Architectural Leadership: Experience leading technical direction for complex systems—moving beyond "notebooks" to scalable, integrated production environments.
Fintech/Regulated Industry Context: (Preferred) Understanding the stakes of "agentic action" in a regulated financial environment.
Start-Up ethos - we look for hungry individuals who seek to make a difference. Mission-ready team players, who are highly accountable for driving themselves, their teams and our business forward.

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