Risk & Credit Analytics Role - Digital Lending FinTech

Key Responsibilities:

- Portfolio Management: Preparing and monitoring of Credit Risk for SME segment.

- Adept in quantitative analysis, data mining, trend analysis and customer profiling.

- Credit Scoring model development, Machine Learning expert with proven track record of end-to-end experience in model development, testing, implementation, and performance tracking.

- Expertise in statistical modeling methods for supervised and unsupervised learning. These methods include (but not limited to) regression analysis, clustering, decision trees, collaborative filtering, nearest neighbours, support vector machines, ensemble methods and boosting, neural networks and deep learning, feature selection, and factorization methods.

- Passion for analytics: Should be able to build cutting edge credit/fraud models using advanced algorithms in SAS or in Big data/Machine Learning environment. Should have hands on experience and track record of delivering projects in individual capacity.

- Process oriented: Should help in building a process that maximizes operating efficiency while maintaining risk across multiple lending cycles. There needs to be an obsession with collecting and analyzing data to drive business iterations and improvements.