Fraud / Credit Data Scientist, Risk Solutions
Core
Build machine learning and statistical models to identify, measure, and mitigate credit, collections, and fraud risk across the client lifecycle.
Role type
Mid-level IC data scientist (risk modeling)
Builds
Automated risk modeling solutions and data pipelines for credit and fraud prevention
Domain
Fintech / Financial Services / Risk Management
Deliverable
production ML models
Required skills
Machine learning, statistical learning, SQL, Python, data transformation, hypothesis-driven analytics, risk factor identification
Preferred skills
MLOps frameworks, cloud environments (AWS Sagemaker), payment processing risk models, credit/fraud domain knowledge
Technologies
Python, R, lightgbm, scikit-learn, pandas, numpy, AWS Sagemaker, SQL
Responsibilities
Design flexible and scalable automated modeling solutions; develop code to combine and transform large volumes of data from disparate sources; synthesize findings into actionable insights for stakeholders; identify opportunities to leverage new ML tools to improve processes; communicate challenges and risks associated with project work
Seniority
Junior to Mid-level, hands-on IC
