Key Responsibilities:

• Design, development and maintenance of credit scoring models for use in core banking products as well as digital lending.
• Full ownership of the model development process from conceptualization through data exploration, model selection, validation, implementation, and business user training and support.
• Work closely with stakeholders to ensure adequate understanding of risk models and their application. Play a key role in the development of products that rely on credit scoring by providing analytics support in the design of product business rules and strategies.
• Work with stakeholders throughout the organization to identify opportunities for leveraging data to drive business solutions using Advanced Analytics for the management of credit risk.
• Development and validation of risk models for use in Loan Pricing, Provisioning, Stress Testing, ICAAP and other applications.
• Understand, measure and manage model risk.
• Assess the effectiveness and accuracy of new data sources, data governance activities (e.g. data quality and cleansing strategies) data gathering techniques and develop processes and tools to monitor, analyze and tune model performance and data accuracy.
• Work with both structured and unstructured data including transforming of large, complex datasets into pragmatic and actionable insights.
• Develop and maintain user and technical documentation/manuals on business requirements, data sources, ETL related activities, data quality assessment, data cleansing activities, data mining analyses, models developed, reports generated and statistical solutions developed and deployed.
• Stay abreast of industry and regulatory trends that may impact new and existing strategy development.

The Person

For the above position, the successful applicant should have the following:

• A bachelor’s degree in mathematics, Business, Statistics, Economics, Actuarial Science, Computer Science or equivalent combination of education and experience.
• Master’s degree in Statistics / Actuarial Science/Data Science/MBA
• Proficiency in Tools, Languages and Techniques like SQL, R, Python, Supervised and Unsupervised Machine Learning Techniques, this a must requirement.
• Experience in SAS, Stata, SPSS, Matlab, Big data technologies (Map/Reduce, Hadoop, Hive, Spark), Deep Learning Techniques will be a bonus qualification

Key Experience Requirements:

• 5+ Years Minimum Experience– (Required)
• Data Science & Statistical Analysis – 5+ years (Essential)
• Machine Learning Algorithms & Techniques – 4+ years (Essential)
• Credit Risk Management – 3+ years (Desirable)
• Banking/Financial Services – 3+ years (Desirable)
• Stakeholder Management – 3+ years (Essential)
• Management Reporting – 2+ years (Desirable)