Data Scientist - Director - Data & Analytics Engineering
Core
Develop statistical and machine learning models to identify, assess, and mitigate fraud risk across Morgan Stanley products.
Role type
Director-level individual contributor data scientist (fraud detection)
Builds
Production ML models for fraud detection and risk mitigation
Domain
Financial services / Fraud detection
Deliverable
production ML models
Required skills
Statistical inference, probability, sampling, hypothesis testing, regularization, bias-variance trade-offs, optimization, feature selection, dimensionality reduction, model calibration, statistical diagnostics, Python, SQL, Hadoop, Hive, Impala, Spark, PySpark
Preferred skills
Fraud detection model development, financial crime analysis, transaction monitoring, payment risk, anomalous-behavior detection, Model Risk Management experience, Tableau
Responsibilities
Independently execute end-to-end model development including technical documentation; Develop and evaluate models for highly imbalanced, non-stationary, and adversarial environments; Apply statistical principles to model selection, validation, and performance assessment; Monitor deployed models, diagnose performance degradation, and recommend recalibration or retirement
Seniority
Director, hands-on IC with mentoring responsibilities
