As a member of Consumer and Community Banking (CCB) Fraud Modeling team, the individual will be responsible for:
- Designing, developing, implementing, and validating statistical models and segmentation for the bank's credit / debit card business
- Perform data extraction, sampling, and statistical analysis/modeling using linear regression, logistic regression, time series analysis/forecasting, multivariate analysis (i.e. clustering analysis, principal component analysis, discriminate analysis, e.tc) and advanced data mining techniques
- Analyze and interpret financial data using SAS and other statistical software in UNIX environment
- Provide and present model results, insights and recommendation to senior management and partners using MS Office (i.e. PowerPoint, Word, and Excel);
- Partner with internal teams to implement models/segments/tools into system and to support business execution and/or analytics on revenue growth and loss control will be responsible
- Master in Statistics, Econometrics, Operations Research, Mathematics and Physics (or equivalent quantitative fields)
- Minimum 1+ years of relevant analytics/modeling experience or solid advanced academic researches. Financial industry experience, especially in credit card / debit card.
- Strong analytical and problem solving skills with the ability to interpret complicated and large amounts of data with business insights
- Prior experience in mentorship/ managing 1-3 people
- Knowledge and experience developing Fraud Models using regression (Logistic, Decision tree, time series, etc.), pattern recognition and/or data mining techniques
- Experience in SAS and SQL in UNIX environment, database such as ORACLE/TERADATA
- Excellent written and oral communication skills to clearly present analytical findings and make business
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