Summary

Applied data scientist role focused on fraud prevention within Creditspring's underwriting data science team. The role uses Python, SQL, scikit-learn, pandas, numpy, Jupyter, and AWS to develop fraud, identity resolution, and credit scoring models for a UK consumer lending business.

Responsibilities

• Collect and analyse internal and external datasets
• Develop fraud and credit scoring models
• Design identity resolution machine learning models
• Run retro analyses, a/b tests, and proofs of concept
• Evaluate fraud modelling techniques and detection methods
• Test and integrate external api feeds
• Monitor and visualise fraud performance metrics