Description

You will develop and deploy machine learning scorecards to manage credit and fraud risk.

Responsibilities

• Build scorecards using machine learning algorithms including Random Forest, Gradient Boosting, XGBoost, and Deep Learning for credit risk, fraud risk, and portfolio management.
• Coordinate with Product, Technology, and Risk functions to align technical development with business needs.
• Automate model development processes, focusing on documentation and turnaround time.
• Liaise with Data and Systems teams to ensure accurate and rapid deployment of ML solutions.
• Analyze financial statements and credit reports for underwriting assessments and implement risk strategies.

Required Skills

• 5+ years of experience in data analytics, model development, validation, or strategy formulation.
• 3+ years of hands-on experience in model development using R, Python, SAS, or SQL.
• Expertise in Risk Management or Credit Risk domains.
• Proficiency in data processing and machine learning implementation.
• Strong analytical skills with the ability to translate ML insights into business intuition.
• Experience analyzing credit reports and financial statements.
• Proven ability to take project ownership and manage credit functions.

Preferred Skills

• Domain expertise in Credit Lending.

Key Skills

Education

Any Graduate