Lead Risk Analytics

Responsibilities:

• Conduct Portfolio Analysis and Monitor Portfolio delinquencies at a micro level, identifying segments, programs, locations, and profiles that 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 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.
• Create a deep level understanding of the various data sources.
• Should be able to understand the business problems and help convert them into analytical solutions.

Requirements:

• Bachelor's degree in Computer Science, Engineering or a related field from a top-tier institution.
• 4-9 years of experience working in Data science/Risk Analytics/Credit Risk/Fraud Risk.
• 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.
• Deep understanding of statistical concepts including descriptive analysis.
• 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 SME/LAP/Secured lending experience is preferred.
• Should have a good understanding of various unsecured credit products.