Senior Lead Data Scientist Fraud

Salary: £48,000 - 70,000 per year Requirements: • End-to-end ML ownership across the full stack, including data engineering, feature development, model design, training, low-latency production deployment, monitoring, and retraining • Strong instinct for when a model is ready for production and when it is not • Proven track record of building ML models and pipelines from scratch, not integrating or extending someone elses product or tooling • Experience building real-time or near-real-time inference systems; batch pipelines alone are insufficient • Comfortable working with large-scale datasets including hundreds of millions of transactions and high-dimensional feature spaces • Strong Python and SQL skills with hands-on experience in scikit-learn, LightGBM, Docker, Jenkins, and modern Python packaging • Self-motivated, fast-moving, and creative, with the ability to bring novel solutions where others reach for off-the-shelf tooling • Ability to communicate precisely across technical and non-technical audiences, including senior stakeholders • Degree in computer science, physics, applied mathematics, astrophysics, automatic control, mathematics, software engineering, electrical engineering, or a related quantitative field Responsibilities: • Rebuild our fraud detection systems from the ground up • Build best-in-class machine learning systems from raw data through feature engineering, model design, training, and real-time production deployment • Convert existing rules-based fraud systems into sophisticated, model-driven architectures operating at scale across hundreds of millions of transactions • Build infrastructure from scratch rather than maintaining or extending existing frameworks • Work with engineers, analysts, and commercial stakeholders to translate ambiguous business problems into precise technical solutions • Bring novel approaches such as graph networks, anomaly detection, and behavioural signals into production where they create real impact Technologies: • AWS • CI/CD • Docker • Jenkins • Machine Learning • Python • SQL • Cloud • Lambda • Fine-tuning More: We are a big company that still moves like a startup, with fast decisions, real ownership, and models that ship. We are rebuilding our fraud detection systems and offer the full mandate to do it right, from raw data to production models, at a scale that affects hundreds of millions of transactions. This is a highly technical role in one of our most demanding problem spaces, based in London on a full-time basis, with opportunities to work on infrastructure and machine learning systems from the ground up alongside engineers, analysts, and commercial stakeholders. Optional experience with early-stage startups, graph neural networks, anomaly detection, behavioural biometrics, AWS, CI/CD, and mentoring other data scientists is valued. Please include a CV in English. last updated 36 week of 2026