Assistant Manager - Model Development

Job Summary

The incumbent will be responsible for developing data-driven, analytically rigorous solutions that enable informed and timely decision-making across the credit lifecycle at Godrej Capital. The role involves building machine learning models, improving analytical processes, driving automation, and contributing to advanced risk intelligence initiatives. A strong passion for modelling, experimentation, and problem-solving is essential.

Responsibilities

• Model Development Advanced Analytics. Develop and implement credit risk models (PD, LGD, EAD), fraud detection algorithms, collection prioritization models, customer propensity models, and other machine learning-based solutions. Apply statistical techniques and ML algorithms to solve complex business problems across underwriting, portfolio monitoring, and collections.
• Insight Generation Risk Monitoring. Identify data patterns, uncover trends, and generate actionable insights to strengthen credit decision-making. Perform deep-dive analysis on emerging customer behavior and macro trends to support early warning signals and risk mitigation strategies.
• Data Engineering Process Improvement. Collaborate with technology teams to enhance data pipelines, improve data quality, and enable scalable model deployment. Contribute to the design, testing, and implementation of production-grade analytical systems.
• Stakeholder Management. Present analytical findings, recommendations, and model outcomes to business, risk, and leadership teams in a clear and structured manner.
• Innovation Alternate Data Exploration. Explore and evaluate alternate data sources to identify new opportunities for credit risk optimization, segmentation, and underwriting enhancements.

Requirements

• Experience: 2-4 years of relevant experience in risk analytics, preferably in BFSI.
• Education: Bachelor's or Master's degree in Engineering, Economics, Statistics, Mathematics, or any quantitative discipline.
• Strong proficiency in SQL for complex data extraction and analysis.
• Hands-on experience in Python and familiarity with industry-standard ML libraries.
• Prior exposure to statistical modelling, scorecard development, or policy analytics.
• Excellent presentation and communication skills for translating analytical output into business insights.
• Experience mentoring junior team members (preferred but not mandatory).
• Work Experience: 2-4 years.

Education

Bachelor's or Master's degree in Engineering, Economics, Statistics, Mathematics, or any quantitative discipline.

Key Skills

• Python
• SQL
• Machine learning
• Credit risk modelling (PD/LGD/EAD)
• Fraud detection
• Scorecard development
• Data pipelines
• Data quality
• Production-grade analytical systems

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