Lead SME - Risk

Responsibilities:

• Conduct portfolio analysis and monitor portfolio delinquencies at a micro level, identifying segments, programs, locations, and profiles that are delinquent or performing well.
• Help 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 opportunities to further increase the quality of the portfolio.
• Work with the product team and engineering team to help implement the risk strategies.
• Work with the data science team to effectively provide inputs on the key model variables and optimize the cutoff for various risk models.
• Create a deep-level understanding of the various data sources (traditional as well as alternative) and optimum use of the same in underwriting.

Requirements:

• Should have a good understanding of various unsecured credit products.
• Should be able to understand the business problems and help convert them into analytical solutions.
• Bachelor's degree in computer science, engineering, or a related field from a top-tier institution (IIT/IIIT/NIT/BITS).
• 6+ years of experience working in data science/risk analytics/risk management, with experience in building 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, and probability distributions.
• Proficiency with statistical and data mining techniques.
• Proficiency with machine learning techniques such as decision tree learning, etc.
• Should have experience working with both structured and unstructured data.
• Fintech or retail/SME/LAP/secured lending experience is preferred.