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.

Experience
5-8 yrs