Lead Data Scientist – Recieve Risk

Overview

As Lead Data Scientist on the Receive team in London, you will shape predictive models and data solutions that improve how customers receive and add money with Wise. You’ll work across engineering, product, analytics and risk to drive decisioning and customer outcomes at scale. Your work directly supports Wise’s mission to move money securely, efficiently and globally. You’ll deploy end-to-end models, build robust data pipelines and stay ahead with state-of-the-art techniques, including fraud prevention, in a fast-paced, cross-functional environment.

Pay / Benefits

• Stock options in a profitable company
• Hybrid working model
• Annual personal development budget
• Visa and relocation support

Responsibilities

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

Key requirements

• Proven track record of deploying models from scratch (data preprocessing, feature engineering, model selection, evaluation, monitoring)
• Strong Python knowledge; ability to justify design decisions; experience with Git/GitHub and reading Java code
• Experience with large datasets and data processing tech (Hadoop, Spark, SQL)
• Familiarity with anomaly detection, supervised/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 settings
• Excellent communication skills and problem-solving ability

• strong communication
• cross-functional collaboration
• problem solving
• Python
• Git (GitHub)
• Java reading ability

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