•Develops Risk Segmentation models by deploying sophisticated statistical techniques like CHAID, cluster analysis, pattern recognition etc. for credit abuse/first party fraud risk discrimination at Acquisition and Existing Customer Management stages
•Work inestablishing the swap set analysis and P&L optimization using the models
•Hands on experience of Credit/Fraud Risk strategy development.
Preferred knowledge of credit/fraud risk analytics
•Work closely with cross functional teams, including business stakeholders, MRM and governance teams, and strategy implementation teams. Implement initiatives to ensure consistency and compliance with global credit policies
•Observe key credit abuse trends, threats, inaccuracies and drivers of those observations. Support Audit requirements from external/internal auditors & queries from Independent Risk
•Strong analytic, strategic and project management skills
•Create story boards, presentations and project plans for discussions with senior management and governance requirements to drive insights
•Utilize UNIX and Statistical Analysis System (SAS) to perform risk, financial and data analyses including profiling, sampling, reconciliation, and hypothesis testing
•Knowledge and experience of statistical procedures and financial analytic tools. (SQL, R, Python, Hadoop, Spark, SAS) and Machine Learning knowledge preferred
• Experience in pre /post validation of deployed strategies and modelsand monitoring of strategy performance against established benchmarks.
•4+ years of relevant experience
•Advanced Degree (Masters required) in Statistics, Applied Mathematics, Operations Research, Economics, MBA (Finance), or other highly quantitative discipline
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Job Family Group:
Decision Management------------------------------------------------------
Job Family:
Business Analysis------------------------------------------------------
Time Type:
Full time------------------------------------------------------
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Qualified applicants will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
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