Related skills
sql python pandas scikit-learn credit risk📋 Description
- Develop and deploy ML models for credit risk and fraud
- Design and optimize data pipelines for production deployment
- Monitor production scores; define metrics and evaluation
- Run experiments (A/B tests) to improve risk outcomes
- Collaborate with Risk, Fraud, Product, and Eng teams
- Explore AI/LLM applications in lending
🎯 Requirements
- 3+ years in data science for credit risk or fraud
- Production-ready systems in fintech startups
- Bachelor’s degree in Math/Stats/Engineering/CS
- Strong math and sampling techniques for finance
- SQL for data; Python (pandas, scikit-learn, xgboost)
- Git/GitHub for code reviews and collaboration
🎁 Benefits
- Meaningful, growth-focused opportunities
- Competitive compensation and equity
- Ownership culture and world-class team
- Impactful problems in Colombia
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