Head of Data Science

About This Opportunity

We are representing a confidential payments technology company in their search for a Head of Data Science to establish and lead their data science function from the ground up. This is a founding role based in the UK (remote available).

Our client operates as a merchant of record serving thousands of software businesses globally. Their unique data position combines subscription, pricing, and granular payment-outcome data across their customer base. Your mandate will be to transform this into economic value by deploying machine learning and agentic systems into production.

This is not a theoretical or analytics-support role. You will own automated decisioning systems inside the product—traditional ML and agentic systems alike—and be accountable for their performance, uptime, and business impact.

Responsibilities

In your first quarter, you'll pressure-test existing hypotheses, size opportunities across payment performance, revenue recovery, sales operations, growth intelligence, and risk/compliance, and determine where to start. Then you'll:

• Personally deliver the first end-to-end system: analysis, feature engineering, model or agent development, deployment, shadow testing, and A/B validation
• Operate what you deploy—own monitoring, retraining, drift response, incident handling, and rollback for live decisioning systems
• Work across both traditional ML (propensity models, uplift models) and agentic systems (tool design, prompt iteration, evals, trace observability), choosing the right approach for each problem
• Establish the production stack alongside platform and engineering teams: reproducible pipelines, model registry, inference services with real SLAs, feature stores, eval harnesses, and monitoring
• Build and lead a hub-and-spoke team of senior data scientists and ML engineers once initial use cases prove out
• Own value capture end to end—shadow-test and A/B test every deployment, translate metric movement into financial impact co-signed by Finance, publish quarterly value reports
• Set governance for automated decisioning in compliance with GDPR, EU AI Act, and payments regulations
• Define boundaries with adjacent functions (product science, analytics engineering, data platform, AI enablement) to keep accountability clear
• Embed cross-functionally with product owners, domain experts, and engineers rather than handing models over the wall

What We're Looking For

Essential:

• Proven experience leading data science or ML teams that own systems in production, with deployments that moved commercial metrics and remained operational
• Currently hands-on with SQL, Python, feature engineering, and model/agent evaluation—you'll be doing this work yourself in the first quarters, not reviewing others
• Experience across both traditional ML and agentic systems, with clarity on when to use propensity models versus tool-enabled agents
• Track record of running live systems: monitoring, retraining, incident response, rollback, on-call responsibility
• Pragmatic about method—willing to deploy rules or heuristics where they capture value, reserving models and agents for problems that justify them
• Comfortable starting with an undefined roadmap, forming your own view backed by numbers, and defending it to executives
• Strong on measurement: experimentation design, uplift modelling, back-testing, financial value attribution that withstands Finance scrutiny
• Fluent in production ML and agent engineering: training pipelines, model registries, inference services, feature stores, drift detection, trace observability
• Able to hire, level, and develop senior talent while setting standards for a new function
• Credible with executives and commercial stakeholders on prioritisation and value estimation

Highly Valued:

• Background in payments, fintech, subscriptions, high-volume operations, or regulated transactional domains
• Experience treating regulated ML as a design constraint: model risk assessment, DPIAs, auditability, version traceability

How We Work With You

Candidates apply directly through Get A Job.ai. Our talent team will conduct an initial screening to understand your background and confirm alignment with the role requirements. Once we've qualified your candidacy, we'll submit your profile to our client for consideration.

Important: Please do not attempt to contact the client directly. All communication and interview coordination will be managed through Get A Job.ai to ensure a professional and structured process.

Pay

Compensation details will be discussed during the screening process and are competitive for a senior leadership role in the UK fintech sector.

Equal Employment Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome applications from candidates of all backgrounds and will accommodate any needs during the application process. Please inform our team if you require support.