Lead Machine Learning Engineer

We are looking for a Lead ML Engineer to provide technical leadership for the development and industrialisation of Scores & Attributes across multiple international markets. You will report to the Head of Analytics Product Development - EMEA and APAC. You will work at the intersection of machine learning, data engineering and platform engineering, helping transform analytical innovation and large-scale data assets into reusable, governed and production-ready capabilities.

You will lead the technical journey from data exploration and attribute development through testing, governance, deployment and production execution. An important part of the role will design reusable architectures and integration patterns that allow these capabilities to grow across markets and existing technology environments.

This is a hands-on technical leadership role: you will combine architecture and engineering leadership with direct contribution to complex implementations. You will mentor engineers and data scientists and establishing standards that help teams to operate independently.

What you will do:

ML Engineering & Attribute Industrialisation

Lead the design and evolution of capabilities for developing, calculating, testing, governing, deploying and operating data attributes at scale. Build reusable frameworks, tooling and automation that allow attributes to move from experimentation and prototyping into governed, production-ready services. Ensure solutions meet requirements for performance, scalability, reliability and maintainability.

Technical Architecture & Platform Integration

Shape the end-to-end technical architecture and engineering patterns supporting the attribute lifecycle - from development in analytical environments through governance and deployment to production execution. Design integration patterns that allow attribute services to work with existing data and bureau platforms while minimising implementation effort for consuming systems. Lead performance and scalability validation and resolve complex cross-platform integration challenges.

Data & Attribute Innovation

Evaluate new data sources and methodologies, quantifying their incremental predictive and analytical value. Develop and implement approaches for demonstrating the value of Experian data assets and translating them into new attributes and capabilities. Explore technical approaches such as synthetic data to support analytical experimentation, product development and data propositions.

Data Engineering & Asset Onboarding

Design reusable approaches for onboarding new data assets and existing attribute libraries, including data ingestion, transformation and ETL pipelines. Establish data-quality controls and engineering practices. Develop approaches for migrating legacy attributes and data processes onto strategic platforms while maintaining business continuity.

Technical Leadership & Market Enablement

Provide hands-on technical leadership for complex implementations and proof-of-concepts across multiple markets. Establish reference architectures, reusable implementation patterns, engineering standards and development practices that can be adopted across teams. Conduct architecture and code reviews, troubleshoot complex technical issues, mentor engineers and data scientists, and help local Analytics and Engineering teams to adopt new capabilities and operate them independently.

Department: Analytics
Function: Information Technology
Experience Level: Not Applicable