Description

Own credit risk model maintenance and optimization across the customer lifecycle, including acquisition, fraud detection, portfolio management, and cross-selling. Analyze trends, patterns, and correlations to inform risk decisions. Evaluate diverse data sources—bureau data, alternative data, and digital footprints—to enhance risk assessment accuracy.

Responsibilities

• Maintain and optimize credit risk models for portfolio performance and fraud detection.
• Analyze large datasets to identify trends influencing credit risk decisions.
• Develop reports and dashboards to communicate key risk metrics to stakeholders.
• Support data validation, model monitoring, and performance tracking.
• Collaborate with business teams to refine risk policies and decision frameworks.

Required Skills

• 5-10 years of experience in analytics, preferably within credit risk or financial services.
• Strong proficiency in Python for data analysis and modeling.
• Expertise in SQL and MySQL for querying large datasets.
• Experience with statistical modeling and predictive analytics.
• Understanding of credit risk modeling and portfolio analytics.
• Ability to interpret data trends and provide actionable business insights.
• Familiarity with data visualization tools.

Preferred Skills

• Experience working with alternative data sources and digital footprints.

Key Skills

Education

Any Graduate