Data Scientist
Core
Deliver end-to-end machine learning solutions for fraud detection, risk scoring, and anomaly detection to strengthen risk management frameworks.
Role type
Senior IC machine learning engineer (fraud detection)
Builds
Production ML models for fraud and risk analytics
Domain
Financial services / Financial crime
Deliverable
production ML models
Required skills
Python (NumPy, Pandas, Scikit-Learn), XGBoost, Random Forest, Gradient Boosting, end-to-end ML lifecycle management, model deployment, large-scale dataset analysis, feature engineering, model explainability
Preferred skills
Banking/FinTech domain experience, real-time fraud detection systems, big data technologies (Spark, Hadoop), MLOps frameworks, regulatory compliance knowledge
Technologies
XGBoost, Random Forest, Gradient Boosting, Spark, Hadoop, Docker
Responsibilities
Develop and implement ML models for fraud detection and risk scoring; Analyze large datasets to identify fraud patterns; Deploy models into production and monitor performance; Build reusable, scalable ML pipelines; Collaborate with business and compliance teams to translate requirements into solutions
Seniority
Senior, hands-on IC
