Roles & Responsibilities:
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Conduct Portfolio Analysis and Monitor Portfolio delinquencies at a micro level, identification of segments, programs, locations, and profiles which are delinquent or working well.
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Helps to develop credit strategies across the customer lifecycle (acquisitions, management, fraud, collections, etc.)
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Identify trends by performing necessary analytics at various cuts for the Portfolio
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Provide analytical support to various internal reviews of the portfolio and help identify the opportunity to further increase the quality of the portfolio
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Work with Product team and engineering team to help implements the Risk strategies
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Work with Data science team to effectively provide inputs on the key model variables and optimise the cut off for various risk models
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Create a deep level understanding of the various data sources (Traditional as well as alternate) and optimum use of the same in underwriting
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Should have good understanding about various unsecured credit products
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Should be able to understand the business problems and helps convert them into the analytical solutions
Required skills & Qualifications:
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Bachelors degree in Computer Science, Engineering or related field from top tier (IIT/IIIT/NIT/BITS)
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2-5 years of experience working in Data science/Risk Analytics/Risk Management with experience in building the models/Risk strategies or generating risk insights
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Proficiency in SQL and other analytical tools/scripting languages such as Python or R
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Deep understanding of statistical concepts including descriptive analysis, experimental design and measurement, Bayesian statistics, confidence intervals, Probability distributions
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Proficiency with statistical and data mining techniques
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Proficiency with machine learning techniques such as decision tree learning etc.
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Should have an experience working with both structured and unstructured data
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Fintech or Retail/ SME/LAP/Secured lending experience is preferred
Employment Type: Full Time, Permanent
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