Tech Stack

Description

As a Senior Data Scientist on the Credit Risk modeling team, you will develop and improve predictive models that inform risk assessment and decisioning. You'll leverage advanced machine learning techniques and a variety of data sources to drive incremental improvements in accuracy, robustness, and coverage, while collaborating with engineering teams to ensure production readiness.

Requirements

• 5-8+ years experience building and deploying predictive models in production
• Strong experience with modern ML techniques (LightGBM/XGBoost, neural networks, representation learning)
• Excellent statistical intuition and comfort with bias/variance tradeoffs and experimental validity
• Fluency in Python and SQL with production-quality coding standards
• Bachelor's degree in Computer Science, Statistics, Math, or related field

Responsibilities

• Improve core credit and risk models through incremental advancements in accuracy, robustness, and coverage
• Leverage structured and unstructured data sources across multiple modalities to drive sustained improvements
• Design, train, and deploy advanced ML models including gradient boosting, representation learning, embeddings, and transformers
• Build rigorous evaluation frameworks using offline validation, backtests, simulations, and online experiments
• Partner with data engineering and platform teams to ensure models are production-ready, scalable, and monitorable