Data Scientist
Core
Develop statistical and machine learning models to identify, assess, and mitigate fraud risk across Morgan Stanley products in highly imbalanced, non-stationary, and adversarial environments.
Role type
Director-level Data Scientist (Fraud Risk)
Builds
Robust, scalable modelling solutions for fraud detection and risk mitigation
Domain
Financial Services / Fraud Detection / Machine Learning
Deliverable
production ML models
Required skills
Statistical inference, Python, SQL, Feature engineering, Model validation, Class imbalance handling, Model monitoring, Technical documentation
Preferred skills
Fraud detection domain expertise, Regulated environment experience, Tableau, Data visualization
Technologies
Hadoop, Hive, Impala, Spark, PySpark
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 feature engineering; Partner with stakeholders to implement scalable modelling solutions
Seniority
Director, hands-on IC with mentorship
