I build machine learning systems that power lending and payment decisions for millions of users. Currently focused on credit risk modeling, fraud detection, and production ML infrastructure.
- Production ML systems for digital lending (1m+ users, $2m+ loan volume)
- Real-time fraud detection for payment platforms
- Scalable credit risk models with ensemble methods
- ML infrastructure for regulated financial services
- Credit Risk Modeling: Ensemble methods, scorecard development, IFRS 9 ECL forecasting
- Fraud Detection: Anomaly detection, real-time inference, behavioral analytics
- Production ML: Model deployment, monitoring, A/B testing, drift detection
- Financial ML: Regulatory compliance, explainable AI, business-focused metrics
Languages: Python, SQL ML/Data: scikit-learn, XGBoost, LightGBM, pandas, NumPy MLOps: MLflow, Docker, Kubernetes, Airflow Cloud: AWS (SageMaker, Lambda, S3), GCP Databases: PostgreSQL, MongoDB, Redis
- Improved credit approval accuracy by 20% using ensemble ML
- Reduced loan default rates by 16% through advanced risk modeling
- Decreased collections break rate by 18% with behavioral analytics
- Built fraud detection system processing 100k+ transactions daily
- Production ML for fintech
- Credit risk modeling at scale
- Fraud detection architectures
- ML in regulated environments
- LinkedIn: https://www.linkedin.com/in/temidayo-akindahunsi/
- Medium: @Ray_Brix
- X: @Ray_Brix
- Email: temidayoakindahunsi22@gmail.com
💬 "Building ML systems that make financial services more accessible and safer for everyone"