Role Responsibilities
- Develop real time and batch risk models to screen online transactions and stop fraudulent ones
- Document and communicate model results and insights internally
- Support Senior/Staff Risk Scientists with ad-hoc analysis in response to internal and external requests
- Continuously track and evaluate the effectiveness of risk models and rules
- Analyze online transaction activity to identify loss reduction opportunities and devise actionable plans to exploit such opportunities
- Profile customer behavior to identify opportunities to enhance model/rule performance
Role Requirements
- Preferably Master's degree or Graduate degree in quantitative related field (Statistics, Math, Operations Research, MS, M-tech, B-tech etc) required with proven track record in using advanced quantitative and statistical technique. Minimum bachelor’s degree in quantitative field required.
- 3+ years of relevant experience. Data analytics related Master thesis or certified coursework projects will add additional value.
- Strong problem solving and analytical skills
- Strong communication skills to convey fraud insight
- Ability to analyze problems and produce justification to enhance fraud decisions.
- SQL and at-least one of the Python/R programming experience and aptitude to learn on the job.
- Working knowledge of developing predictive models like logistic regression, decision tree etc and machine learning techniques
- Intermediate knowledge of Microsoft Excel/Power BI/PPT
- Exposure to cloud systems like AWS Sagemaker/ Dataiku is preferred