Data Scientist – Credit Cards

Overview

In this role you will build and validate credit card risk, pricing, and customer lifetime value models for iwoca’s business card. You will work with small samples and incomplete data, applying Bayesian methods to quantify uncertainty and inform decisions. You will own projects from framing questions to deployment, collaborating with the Credit Cards team and sharing methods with the broader analytics guild. This is a hands-on role at the intersection of product, risk, and data science, shaping how the card grows.

Pay / Benefits

• Flexible working hours
• Medical insurance from Vitality
• Private GP service for you, partner, and dependents
• 25 days’ holiday + birthday day + buy/sell extra days
• One-month fully paid sabbatical after four years
• Employee equity incentive scheme

Responsibilities

• Analyze and model commercial decisions for the card using Bayesian methods to handle small samples and uncertainty
• Own projects from framing business questions to delivering actionable insights
• Quantify uncertainty in estimates and explain implications for decision-making
• Collaborate with Credit Risk Modelling and analytics guild to share methods
• Design and assess mechanisms for card limits, pricing, and cross-product interactions
• Translate analytical results into business actions and measurable impact

Key requirements

• Statistical foundations in probability and statistics
• Bayesian reasoning with priors, updating, and hierarchical models
• Analytical ownership from problem framing to decision delivery
• Business curiosity and ability to connect analysis to customer economics
• AI leverage to build prototypes, automation, or modeling pipelines
• Clear, concise communication tailored to non-technical stakeholders

• Clear and concise communication
• Curiosity about business problems
• Ability to work collaboratively with cross-functional teams
• Bayesian modeling and hierarchical models
• Priors and updating in real-world contexts
• Python coding for analyses and pipelines

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