Data Engineer, Fraud Predictive Analytics
Core
Develops predictive models and intelligent automation for fraud detection, investigation, and prevention using advanced analytics and machine learning.
Role type
Senior Data Engineer (Fraud Predictive Analytics)
Builds
Fraud detection, investigation, and prevention tools/models for the Financial Crimes Unit
Domain
Financial Services / Fraud Analytics
Deliverable
production ML models
Required skills
SQL, Python, PySpark, XGBoost, H2O, SparkML, statistical analysis, multivariate testing, optimization algorithms, pattern detection
Preferred skills
Experience building fraud models for large Financial Institutions, deep learning, artificial intelligence
Technologies
SQL, Python, PySpark, XGBoost, H2O, SparkML
Responsibilities
Conduct research to identify and recommend solutions for financial crimes risk exposures; Support data collection, integration, and retention requirements; Apply statistical and machine learning techniques to test and refine hypotheses; Diagnose and resolve predictive model performance issues; Work with data owners to select and assemble source data into prepared datasets.
Seniority
Senior, 5-7 years experience
