Senior Data Scientist, Predictive Modeling, Credit & Risk

What you'll do

• Improve core credit and risk models through incremental advancements in accuracy, robustness, and coverage.
• Leverage structured and unstructured data sources to drive sustained improvements in model decision quality.
• Design, train, and deploy advanced machine learning models including gradient boosting and transformer-based approaches.
• Build and apply rigorous evaluation frameworks such as backtests, simulations, and online experiments.
• Partner with data engineering and platform teams to ensure models are production-ready and scalable.
• Translate successful modeling work into reusable patterns and abstractions for use across other teams.
• Serve as a technical leader through design reviews, code reviews, and informal mentorship.

What we're looking for

• Bachelor's degree in Computer Science, Statistics, Math, Quantitative Economics, or a similar field from an accredited undergraduate institution.
• 5-8+ years of experience building and deploying predictive models in production environments.
• Demonstrated track record of delivering and iteratively improving models in production rather than just offline development.
• Strong experience with modern machine learning techniques including LightGBM, XGBoost, and neural networks.
• Fluency in Python and SQL with production-quality coding standards.
• Excellent statistical intuition regarding bias/variance tradeoffs, generalization, and experimental validity.
• Proven ability to take ambiguous modeling problems from the idea stage to production impact.
• Hands-on experience with embeddings, transformers, or deep representation models (preferred).