We are hiring for the Analytics Division in the US.
This is mandatory for you to apply only if you already have a WORK VISA for the US or if you are a US CITIZEN. If you are NOT eligible then do not apply for the job.
ROLE AND RESPONSIBILITIES DESCRIPTION:
- Drive collection initiatives aimed at reducing loss, collection cost and minimizing exposure to risk, across all due buckets
- Knowledge and experience in applying data to solve business problems through quantitative analysis. Experience with predictive modeling, optimization and similar data-driven business solutions
- Design Loss Forecasting Models to predict impact on Delinquency and Losses
- Design portfolio segmentation using quantitative as well as qualitative objective function
- Optimize Collections Treatments channels across due Buckets for high Collections efficiency and with minimal cost.
- Analyze existing collections programs to identify areas of opportunity and make recommendations or propose solutions as appropriate
- Design & roll out dashboards to track model/strategy/policy performance.
Essential Competencies:
- 3+ years of experience in Credit Risk / Collections Analysis with a desire to participate in consultative engagements
- Good working knowledge of Databases systems, SQL, SAS, Excel and VBA
- Facilitation skills/ Excellent communication and presentation skills – ability to interact with all levels of management, strong presentation skills with clear and concise communication
- Ability to design analytical solutions for complex business problems
- Experience in handling large data sets and reporting systems
Masters in Quantitative Techniques (Mathematics/ Statistics/ Econometrics/ Operations Research) with 3+ years’ experience in Credit Risk / Collections Analysis with a desire to participate in consultative engagements
Earlier work experience should include:
- Development of forecasting models
- Development of segmentations trees using EM
- Development of predictive models.
NOTE: If you do not have an active work VISA of the US please do not apply.
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