ANALYTICS DATA MODELER
Core
Execute the technical component of assigned analytical projects, including data preparation, model development, validation, automation, and monitoring under the leadership of an Analytics Consultant.
Role type
Senior IC data modeler (credit risk & financial services)
Builds
Statistical, econometric, and machine learning models for the credit cycle (origination, maintenance, collection, recovery, fraud, expected loss, provisions, macroeconomic prospectivity)
Domain
Financial services / Credit risk / Machine learning
Deliverable
production ML models
Required skills
Python, SQL, Spark/PySpark, statistical modeling, machine learning, regression, classification, clustering, time series analysis, survival analysis, calibration, validation, Git, reproducible notebooks, Azure Databricks, data automation, large-scale data processing
Preferred skills
Credit risk domain expertise, provisioning systems experience
Technologies
Python, SQL, Spark, PySpark, Git, Azure Databricks
Responsibilities
Develop statistical and machine learning models for the credit cycle; Apply methodological, regulatory, and business specifications to create reproducible technical solutions; Implement controls over data, samples, code, calculations, and results to ensure consistency and quality; Automate repetitive processes and build reusable components; Monitor model performance and documentation; Utilize AI tools as authorized technical support under human validation and information protection policies.
