Credit Risk Data Scientist

Credit Risk Data Scientist focuses on deliver innovative predictive models into our modern aws production environments.

What the role involves

• Deliver innovative predictive models into our modern AWS production environments.
• Work alongside our lead data scientist to experiment, engineer.
• Predictive Modelling (Linear & Non-Linear): You will build.
• Maintain foundational Linear Regression models for credit, affordability, and fraud scoring, while developing advanced XGBoost models for deeper risk insights.
• Monitor models in high-scale production.
• As a small, progressive team, we offer the agility to move fast and the autonomy to lead your own projects.

Skills and requirements

• Core Data Science: Advanced ML: Experience with boosting models is essential for our higher-complexity tasks.
• Natural Language Processing (NLP): GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour).
• Data Engineering: Strong SQL skills and experience building data pipelines.
• Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc.).

Confirmed role details

• Primarily remote and flexible, collaborating in the central London office at least 2 days per week.

Additional role context

• Infact are a progressive, fast-moving, credit referencing start-up.
• We see great opportunities to combine foundational statistics with modern AI to find meaning in consumer finance data.
• We operate a pragmatic stack where Linear Regression remains vital for stability and baseline performance, while XGBoost and LLMs are used as responsible additions.