Lead Data Scientist - Fraud Risk at Wise
United Kingdom
Posted
on-site · full-time · Visa sponsorship
Responsibilities:
- Lead design, development and production deployment of ML models to detect and mitigate fraud across Receive product flows.
- Analyse large transaction, customer and product datasets to identify patterns, risks and improvement opportunities.
- Own experiment design and A/B testing to validate decisioning changes and product improvements.
- Build scalable feature pipelines and production-ready models with robust monitoring and alerting.
- Collaborate closely with engineering, product, analytics, operations and risk teams to translate business needs into data solutions.
- Drive model lifecycle practices: validation, bias checks, performance monitoring and retraining strategies.
- Mentor peers and contribute to team practices, code reviews and technical design decisions.
Requirements:
- Proven track record deploying end-to-end ML solutions in production (data prep, feature engineering, modelling, monitoring).
- Strong Python skills and experience with version control workflows (Git/GitHub) and code reviews.
- Experience with large-scale data tools (Spark, Hadoop, SQL) and production data pipelines.
- Solid knowledge of fraud detection, anomaly detection or risk modelling techniques.
- Ability to collaborate with engineers and product teams to deliver scalable services; familiarity reading Java is a plus.
- Strong communication, stakeholder management and problem-solving skills.