Scoring Engineer/Data Scientist

We are seeking an experienced Scoring Engineer/Data Scientist to support a large-scale AI and fraud analytics programme within a regulated insurance environment. This is a hands-on role focused on building, deploying, and maintaining machine learning models and pipelines on Azure.

Role Overview

• Design, build, unit test, and maintain ML models and ML pipelines on the Azure platform

• Support and enhance a fraud analytics platform (Quantexa experience preferred)

• Work closely with solution architects, data engineers, and cross-functional teams

• Deliver analytical solutions using a hypothesis-driven approach

• Translate complex analytical concepts into clear, actionable insights

• Support release activities, defect resolution, and production deployments

• Produce documentation, release notes, and model governance artefacts

Essential Skills & Experience

• Strong experience in machine learning and statistical modelling

• Exposure to fraud, financial crime, compliance, or risk analytics

• Experience building ML pipelines, feature engineering, and working with large datasets

• Hands-on experience with MLOps (CI/CD, model deployment, unit testing)

• Strong SQL skills

• Experience with model governance, explainability, and observability

• Experience using Azure, Azure DevOps, and Git

• Programming experience in Python (Scala desirable)

• Excellent analytical and problem-solving skills

• Eligible for BPSS clearance

• Able to work onsite in London 2-3 days per week

Desirable

• Quantexa platform experience or certification

• Apache Spark experience

• Background in insurance, banking, or financial services

• Experience in enterprise-scale AI or data science programmes