AI & Emerging technologies

Lead Data Scientist

Raylo

London · Greater London · United Kingdom

Overview

Lead Raylo's data science function to design, build, and deploy production-grade ML models that drive credit risk, churn, and recommendations. You will shape the data science strategy, mentor the team, and collaborate cross-functionally to unlock growth as the company scales internationally. Expect to redefine ML workflows with agentic architecture and cutting-edge models, delivering measurable commercial impact. This role combines hands-on technical leadership with strategic vision in a fast-growing, AI-driven business.

Pay / Benefits
  • Fast-track career progression
  • Exclusive Raylo device lease
  • Private medical insurance
  • Stock options for all employees
  • L&D budget for skills
  • Hybrid working model
Responsibilities
  • Own end-to-end design, build and deployment of production-grade ML models (credit risk, churn prediction, recommendations)
  • Partner with product, engineering, risk, operations, and commercial teams to identify high-impact ML opportunities and move them from ideation to action
  • Redesign data science processes around agentic architecture and latest LLM models
  • Shape and grow Raylo’s data science function to scale over the next five years
  • Define and lead the data science roadmap and how AI transforms the data practice
  • Contribute to decision-making and impact by translating complex modelling into clear business value
Key requirements
  • 7+ years in data science and predictive modelling
  • Degree with 2:1 or higher from a top university, preferably STEM or quantitative
  • Production deployment of ML models and practical hands-on technical leadership
  • Experience coaching and growing a data science function while delivering IC-level projects
  • Strong stakeholder management and ability to drive data-driven decision making across diverse teams
  • Ownership mindset and proactive delivery in a fast-paced, cross-functional environment
  • stakeholder management
  • cross-functional collaboration
  • strong communication
  • state-of-the-art ML models
  • production-grade ML deployment
  • credit risk modelling

Reference: WJ-747_31166187 · Posted 01 Nov 2026

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