Indian private sector bank with national presence. Employees over 20,000 people and holds assets worth $22bn.
The analytics team is crucial in delivering the long-term vision of the bank.
The team will work closely with all business units (product, sales), functional stakeholders (e.g. credit, operations, Journey Excellence), technology teams (IT team and vendors) and external partners (e.g. DSAs, agencies) to deliver impact on key business metrics through data and analytics.
Understanding the business nuances and associated fraud patterns.
Developing advance ML models for customer fraud identification
Develop the entire framework comprising of solutions for individual, channel and collusion fraud using a combination of supervised and unsupervised statistical techniques
Explore alternate sources of data which can add value on top of the traditional data sources for fraud prevention
Supporting the business and risk teams with bespoke and strategic analysis
Development, tracking and management of the Fraud prevention strategy across all businesses
Develop and test hypothesis around consumer repayment behaviours for retail products
Develop analytical models to predict the flow of customers from one delinquency bucket to another
Develop key risk parameters for collections and benchmark them month on month
Create and Monitor MIS for all the collection strategies being deployed
Master's degree in Economics, Statistics, Computer Science etc
1-5 years of experience in the field of analytics - preferably in Banks/NBFCI/Fintech/Ecommerce/COnsulting
Proficient in SAS, Python, R
Strong understanding of the statistical concepts and modelling techniques like LR, GBM, XGBoost, Random Forrest, ANN
Experience of working on business/risk analytics
Logical thought process, ability to scope out an open ended problem into data driven solution
Opportunity to work with a fast-growing Indian bank
Be part of analytics team crucial in executing long-term goals of bank