Description

You will build predictive and statistical models to improve credit policy and minimize credit losses.

This role is on-site.

Responsibilities

• Build predictive models to identify potential defaulters and evaluate credit risk in real time.
• Develop statistical models for acquisition, risk management, customer retention, and segmentation.
• Track production model performance and adjust based on findings.
• Conduct forecasting and analysis to account for economic shifts and expected delinquency rate changes.
• Partner with subject matter experts to gather requirements and design data quality procedures.

Required Skills

• 3+ years of strong SQL experience.
• 3+ years of experience using SAS or Python for predictive modeling.
• Hands-on experience in statistical model building, validation, and implementation.
• Ability to perform in-depth research and quantitative assessment of business problems.
• Strong knowledge of core computer science principles, including algorithms and data structures.
• Proven ability to manipulate data and establish links across disparate data sources.
• Bachelor's degree in Computer Science, Statistics, or an equivalent combination of education and experience.

Preferred Skills

• Master of Science in a quantitative field.
• Experience building predictive models within the financial services industry.

Key Skills

Education

Any Gradute