1. Fraud Strategy
- SAS is Must
- Prior experience in development of fraud strategy is must- 2 to 5 years of risk analytics experience. Preferably in Financial/Banking domain.
- Working knowledge of Fraud strategy is desirable; knowledge in Risk segmentation & monitoring, model building and monitoring, Risk strategies will be required.
- Extensive knowledge end-to-end model building process desirable
- Prior experience with retail banking analytics would be preferable
- Strong working knowledge on Statistical Analysis concepts and application
- Exposure to advance analytics applications preferable
- Strong in analytical problem-solving, good in numbers crunching skills
- Strong communication skills (verbal and written)
- Post Graduate degree in quantitative disciplines (Statistics, Economics, Mathematics, Operations Research, Management Science) preferable
- Proficiency in SAS is mandatory. Hands on experience in R, Python and machine learning techniques is desirable.
- The incumbent would be required to provide analytical support Fraud strategy team across unsecured products and all brands
- Drive fraud risk segmentation project independently and end-to-end that needs not only to work on analytical side but also to deal with project complexities and data challenges
- Provide short term adhoc analysis output as per business question to improve efficiency
- See the 'bigger picture' and be able to understand the impact of various strategies, policies and events
- Complete analysis as required and document results and formally present findings to management.
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