Roles & Responsibilities:
- Conduct Portfolio Analysis and Monitor Portfolio delinquencies at a micro level, identification of segments, programs, locations, and profiles which are delinquent or working well.
- Helps to develop credit strategies across the customer lifecycle (acquisitions, management, fraud, collections, etc.)
- Identify trends by performing necessary analytics at various cuts for the Portfolio
- Provide analytical support to various internal reviews of the portfolio and help identify the opportunity to further increase the quality of the portfolio
- Work with Product team and engineering team to help implements the Risk strategies
- Work with Data science team to effectively provide inputs on the key model variables and optimise the cut off for various risk models
- Create a deep level understanding of the various data sources (Traditional as well as alternate) and optimum use of the same in underwriting
- Should have good understanding about various unsecured credit products
- Should be able to understand the business problems and helps convert them into the analytical solutions
Required skills & Qualifications:
- Bachelor's degree in Computer Science, Engineering or related field from top tier (IIT/IIIT/NIT/BITS)
- 1-5 years of experience working in Data science/Risk Analytics/Risk Management with experience in building the models/Risk strategies or generating risk insights
- Proficiency in SQL and other analytical tools/scripting languages such as Python or R
- Deep understanding of statistical concepts including descriptive analysis, experimental design and measurement, Bayesian statistics, confidence intervals, Probability distributions
- Proficiency with statistical and data mining techniques
- Proficiency with machine learning techniques such as decision tree learning etc.
- Should have an experience working with both structured and unstructured data
- Fintech or Retail/ SME/LAP/Secured lending experience is preferred
