About INDmoney:
INDmoney is a fast-growing super finance app revolutionizing the way users manage their investments and finances. As we scale our digital lending vertical, we seek dynamic professionals with a strong background in ML & data science to create, enhance and monitor our risk models and ensure robust underwriting decisions to scale business.
Job Summary:
We are looking for a Data Scientist, with a hybrid background in Data science, Credit Risk model development, Machine Learning and Data analysis. The ideal candidate will build intelligent, data-driven credit risk models with predictive modeling expertise using machine learning & AI. He will play a key role in refining credit strategies, reducing defaults, and driving healthy loan book growth.
Key Responsibilities:
- Develop, validate, and implement credit risk models using credit bureau data, demographic indicators, transactional behavior, and alternative data sources.
- Leverage machine learning, Mathematical and statistical techniques to predict borrower behavior, default probability, and fraud risk.
- Design and refine scorecards and decision engines to automate and scale credit decisions.
- Monitor loan portfolio performance, identify risk trends, and recommend optimization strategies.
- Detect and mitigate fraud by spotting suspicious patterns using advanced analytics.
- Collaborate with Product, and Tech teams to ensure seamless integration of risk models into the lending journey.
- Stay updated on RBI digital lending guidelines and ensure regulatory compliance across risk models.
Qualifications & Skills:
- Bachelor's/Master's degree in Finance, Economics, Data Science, Statistics, or a related field.
- 35 years in Data Science and Credit Risk Analysis.
Must have: The candidate must have an experience in using data science for building lending credit risk models
- Hands-on experience building predictive models for credit risk using tools like Python, R, or similar.
- Machine Learning Data Science Data Analytics Python (Programming Language) Data Visualization SQL Statistical Modeling
- Knowledge of credit bureau reports, financial statement analysis, and alternative credit scoring techniques.
- Experience with fraud detection models and risk-based pricing strategies is a plus.
- Strong problem-solving skills and a keen eye for data patterns and business impact.
