Tech Stack

Description

You will develop and deploy machine learning and statistical models for credit risk and portfolio management, collaborating with cross-functional teams to drive data-driven decisions that directly impact business profitability.

Requirements

• Bachelor's degree in quantitative field; Master's preferred
• 5-10 years experience building ML/statistical models
• Strong SQL and Python skills for large datasets
• Experience with databases (SQL, NoSQL, Hive) and pipelines on SageMaker and Snowflake
• Experience working with Product, Engineering, and Data Engineering teams

Responsibilities

• Develop and deploy ML/statistical models for portfolio management, loss mitigation, and loss forecasting
• Present model performance and insights to Credit, Risk, and Business Unit leaders
• Identify opportunities for advanced modeling approaches
• Collaborate with Model Risk Management to ensure model rigor and governance
• Monitor models via dashboards and KPI tracking