Job Location: New Delhi
- Responsible for development and implementation of world-class credit and fraud risk machine learning models across customer lifecycle (eg underwriting, portfolio management, and collections)
- Building and implementing next-generation, predictive models leveraging traditional and alternate data
- Analysis of existing portfolio, to create optimum pre-acquisition risk strategy, which helps drive better customer behavior and hence increased revenue
- Successfully conceptualize, develop and deploy advanced analytics solutions in a high performing environment through data augmentation, value extraction, and monetization
- Drive data-based decision making by providing actionable insights from customer behavior and engagement across various touchpoints
- Experience working with learning ML models such as linear/logistic regression, clustering, support vector machines (SVM), neural networks, Random Forest, CRF, Bayesian models, etc
- Transaction behaviour analytics, user level analytics and scorecards
- Conduct causality experiments by applying A/B experiments or epidemiological approach to identify the root issues of an observed result
- Understanding of risk data including the bureau data and its uses in development of Risk strategy
- Help build a team of data analysts and create a culture of data led decision making
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