Data Scientist
Core
Develop statistical and machine learning models to identify, assess, and mitigate fraud risk across Morgan Stanley products.
Role type
Director-level Data Scientist (Fraud Risk)
Builds
Fraud detection models, data pipelines, and analytical datasets for financial services clients.
Domain
Financial Services / Fraud Detection / Machine Learning
Deliverable
production ML models
Required skills
Statistical inference, Python, SQL, Feature engineering, Model validation, Class imbalance handling, Data leakage prevention, Model monitoring, Technical documentation
Preferred skills
Fraud detection domain expertise, Regulated environment experience, Tableau, High-volume transactional data analysis
Technologies
Python, SQL, Hadoop, Hive, Impala, Spark, PySpark, Tableau
Responsibilities
Execute end-to-end model development and technical documentation; Develop and evaluate models for imbalanced and adversarial environments; Monitor deployed models and recommend recalibration; Provide technical guidance and mentoring to junior staff; Perform exploratory data analysis and construct analytical datasets; Conduct feature engineering and select ML techniques; Manage model development projects independently.
Seniority
Director, hands-on IC with mentorship
