Lead Data Scientist – Receive Risk

Overview

As Lead Data Scientist on Wise’s Receive team in London, you will design and deploy ML models to improve how customers receive money, while advancing scalable data science capabilities. You’ll work with engineering, product, and risk to inform decisions and enhance customer outcomes. Your work directly supports Wise’s mission to move money faster, easier, and cheaper for millions of users. This role combines hands-on modelling with cross-functional collaboration to drive measurable impact at scale.

Pay / Benefits

• Stock options
• Hybrid working model
• Annual personal development budget
• Visa and relocation support

Responsibilities

• Lead development and deployment of ML models to improve Receive product performance across markets
• Analyze large volumes of customer, transaction and product data to identify trends, risks and opportunities
• Design and implement experiments to evaluate product changes, decisioning systems and customer experience improvements
• Build scalable modelling approaches to support prioritisation, personalization, risk management and operational decisions
• Collaborate with analysts, product managers, engineers, operations and risk teams to translate business requirements into data science solutions
• Develop robust data pipelines, algorithms and tools to support production-grade modelling and decision-making
• Stay updated on advances in data science, ML, and fraud prevention to maintain state-of-the-art capabilities in the Spend domain

Key requirements

• Proven track record of deploying models from scratch (preprocessing, feature engineering, model selection, evaluation, monitoring)
• Strong Python knowledge and ability to justify design decisions; familiarity with Git and code review; ability to read Java
• Experience with large datasets and data processing technologies (Hadoop, Spark, SQL)
• Familiarity with anomaly detection, supervised and unsupervised learning, and real-time data analysis
• Experience with statistical analysis and presenting insights to drive action
• Strong product mindset and ability to work independently in cross-functional environments
• Good communication skills to explain technical concepts to non-technical stakeholders
• Problem-solving skills to refine statements and determine solutions

• Clear communication
• Collaborative mindset
• Proactive problem-solving
• Python
• Git (pull requests, code reviews)
• Java reading ability

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