Analytics Role - R/Python/SAS - Bank

Salary offered: upto 10 LPA

The client is an Indian private sector bank headquartered in Mumbai, Maharashtra, India. the group's flagship company, to carry on banking business.It offers a wide range of banking products and financial services for corporate and retail customers through a variety of delivery channels and specialized subsidiaries in the areas of personal finance, investment banking, general insurance, life insurance, and wealth management.Bank has a network of 1,369 branches across 689 locations and 2,163 ATMs in the country, it was the fourth largest private bank in India by market capitalization.

Job location: Mumbai, Malad East

Experience: 2-3 years if Postgraduate /3-4 years if just BE

Job Requirements:

1. Conduct detailed analysis, create segments, develop predictive models to discover patterns in multiple, large and seemingly unconnected data points and turn them into actionable, business, critical insights

2. Candidate will be required to work closely with Collections and Recovery team, Fraud Unit, Third party products(group products) like insurance, Securities etc. in any of the following areas - Risk Mitigation, acquisitions, campaigns, existing customer management.

3. Develop collection recovery strategies using advanced analytics models and techniques.

4. Develop Fraud detection and mitigation strategies to identify the various type of frauds in(liabilities, Debit Cards, ATM, Credit cards).

5. Should possess strong domain knowledge in areas of Fraud and crime analytics in Bank or credit card industry

6. Should be expert in R/ Python and SAS. The candidate is required to work with hands-on these tools.

7. Should possess strong knowledge of Machine Learning Algorithm, text Analytics/ mining and has proven application in work.

8. The inclination to programming /coding is a plus.

9. Masters in Business, Statistics, Economics, Computer Science, mathematics, Analytics with relevant Experience.

10. If a candidate is only Engineer then BE+ 4 years of relevant analytics, machine learning or big data exposure is the must.