Risk Associate - Protected Partnership

Basic Qualifications :
- Bachelors or Masters degree in, Statistics, Economics, Computer Science, or other Engineering disciplines -3+ 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/Retail lending experience is preferred Key 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 for various co-lending partnerships - Form, manage and execute the policies around risk management for all Co-lending partnerships across products - In conjunction with business team, conduct thorough risk assessments to ensure we onboard the right partners that meet our strategic goals and objectives. - 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 portfolios of different co-lending partners - Work with Product team and engineering team to help implement the Risk strategies - Work with Data science team to effectively provide inputs on the key model variables and optimize 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 help convert them into the analytical solutions