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Lead Data Scientist - Fraud Risk

London, gb💼 Full-time🗓 2026-09-28

Core

Lead the development and deployment of machine learning models to improve Wise's Receive product performance, focusing on risk mitigation and customer outcomes for international payments.

Role type

Senior IC data scientist (fraud risk & payments)

Builds

Production ML models, scalable data pipelines, and decisioning systems for the Receive product

Domain

Fintech, cross-border payments, fraud risk

Deliverable

production ML models

Required skills

Python, large-scale data processing (Hadoop, Spark, SQL), feature engineering, model selection and evaluation, anomaly detection, supervised and unsupervised learning, statistical analysis, code review (Java), MLOps tools

Preferred skills

Fraud domain expertise, LLM-based solution design, Airflow, MLflow, AWS SageMaker/EMR, CI/CD

Technologies

Python, Hadoop, Spark, SQL, Git, GitHub, Airflow, MLflow, AWS SageMaker, AWS S3, AWS EMR

Responsibilities

Lead development and deployment of ML models for the Receive product; Analyze large volumes of customer and transaction data to identify trends and risks; Design and implement experiments to evaluate product changes; Build scalable modelling approaches for risk management; Collaborate with cross-functional teams to translate business requirements into data science solutions; Develop robust data pipelines and tools for production-grade modelling.

Seniority

Senior, hands-on IC

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