Data Scientist and AI Engineer at infact.io

Company Description: Progressive fintech credit startup.

Job Description: You will develop and deploy innovative predictive models to transform consumer credit risk assessment. By balancing foundational statistics with advanced machine learning and Generative AI, you will tackle challenges in affordability, fraud detection, and entity resolution. Your work directly impacts underserved consumers by creating more equitable financial products through explainable data science.

Location: London, UK.

Why this role is remarkable: Rare opportunity to combine traditional linear regression stability with cutting‑edge XGBoost and LLM applications in a high‑stakes production environment. Join a fast‑moving, well‑funded startup backed by expert leadership where you have the autonomy to lead projects from experimentation to containerized deployment. Directly contribute to financial inclusion by building ethical models that use SHAP for transparency, ensuring fair outcomes for everyday consumers.

What you will do:

• Build and maintain foundational linear models and advanced XGBoost architectures for credit, affordability, and fraud scoring.
• Implement NLP techniques and LLM context engineering for large‑scale entity resolution and unstructured data analysis.
• Collaborate with engineering teams on MLOps to containerize and monitor models within a high‑scale AWS cloud environment.

The ideal candidate:

• Holds a degree in a quantitative field with 2+ years of professional experience in Fintech, Finance, or Credit Risk.
• Demonstrates expert‑level Python skills and a deep understanding of statistical assumptions, model interpretability, and bias mitigation.
• Possesses a creative, analytical mindset capable of identifying behavioral clusters and trends within raw, complex datasets without predefined hypotheses.