
Data Science Manager
1 day ago
The organization has been consistently recognized as a Great Place to Work receiving certifications in 2022 and 2023. As it stands, Godrej Capital holds a spot among India's Top 50 Best Workplaces in BFSI 2023 and is also recognized as one of India's Great Mid-Size Workplaces 2023. Beyond that, it has also had the honor of being named the Best Organization for Women by The Economic Times in both 2022 and 2023, and the Best Workplaces for Women by Great Place to Work in 2022 and in 2023.
About the Role:
As a key member of the Modeling Center of Excellence at Godrej Capital, you will drive data-driven initiatives that empower strategic business decisions through model building and implementation. Your expertise will contribute to developing advanced analytical models, optimizing credit risk processes, and implementing innovative solutions that enhance the company's lending operations.
Key Responsibilities:
- Design, develop, and deploy machine learning models and analytical algorithms to support credit risk assessment, behavioral scoring, collection prioritization, customer propensity modeling, and other critical lending decisions.
- Analyze complex datasets to identify patterns, trends, and emerging risks, delivering actionable insights through models that inform business strategies and early warning systems.
- Collaborate closely with technology teams to enhance data infrastructure and optimize business workflows, ensuring seamless integration and production deployment of scalable ML models.
- Lead, mentor, and guide a team of junior analysts and data scientists in delivering high-quality, impactful analytical frameworks and models.
- Explore and incorporate alternative data sources and innovative data-driven techniques to uncover new opportunities and refine credit risk for improved portfolio performance.
Qualifications & Experience:
- 5 to 7 years of professional experience in Risk Analytics or related data science roles, preferably within the BFSI sector.
- Bachelor's or Master's degree in Engineering, Economics, Statistics, Mathematics, or a related quantitative discipline; a preference for candidates with an engineering background.
- Proficiency in SQL for complex data querying and thorough data analysis.
- Strong programming skills in Python and/or R, with hands-on experience applying statistical algorithms and machine learning techniques in real-world business contexts.
- Experience in scorecard development, no-code low code ML development platforms, portfolio monitoring, or policy analytics is highly desirable.
- Prior experience mentoring junior team members is an advantage.
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