Job description

Summary: Lead development and enhancement of analytical and behavioral modeling capabilities to power bank-wide forecasting of customer/account analytics, behavioral modeling, statistical forecasting, and model validation. Key Skills: • Advanced SQL and Python/R programming • Statistical and econometric analysis • Behavioral analytics, segmentation, regression, time series, predictive modeling • Survival/cohort analysis • Data visualization • Strong business translation skills Responsibilities: • Design and implement segmentation methods and analytics to improve deposit forecasting for decay/runoff, attrition, migration, beta, and elasticity methodologies • Develop behavioral and response models for consumer lending and card portfolios, including inputs for utilization, attrition/prepayment, and predictive analytics • Diagnose underlying business performance drivers, statistically explain changes and trends • Provide empirical assumptions and models for sensitivity, base, and stress scenario planning • Integrate behavioral modeling with financial outcomes for business decision support • Manipulate customer/account-level data, conduct feature engineering, data quality assurance, and build analytical datasets • Lead modeling methodology, validation, back testing, and statistical diagnostics as part of model governance • Collaborate with teams across Forecasting, Product, Data/Technology, Finance, Treasury, and Model Risk/Validation Ideal Background: • 7+ years in banking decision science, quantitative analytics, econometrics, data science, or advanced financial analytics • Demonstrated track record in statistical modeling, forecasting, and business translation Lead development and enhancement of analytical and behavioral modeling capabilities to power bank-wide forecasting of customer/account analytics, behavioral modeling, statistical forecasting, and model validation.

Requirements

Must-haves

Advanced SQL and Python/R programming
Statistical and econometric analysis
Behavioral analytics, segmentation, regression, time series, predictive modeling
Survival/cohort analysis
Data visualization
Strong business translation skills
Design and implement segmentation methods and analytics to improve deposit forecasting for decay/runoff, attrition, migration, beta, and elasticity methodologies
Develop behavioral and response models for consumer lending and card portfolios, including inputs for utilization, attrition/prepayment, and predictive analytics
Diagnose underlying business performance drivers, statistically explain changes and trends
Provide empirical assumptions and models for sensitivity, base, and stress scenario planning
Integrate behavioral modeling with financial outcomes for business decision support
Manipulate customer/account-level data, conduct feature engineering, data quality assurance, and build analytical datasets
Lead modeling methodology, validation, back testing, and statistical diagnostics as part of model governance
Collaborate with teams across Forecasting, Product, Data/Technology, Finance, Treasury, and Model Risk/Validation
7+ years in banking decision science, quantitative analytics, econometrics, data science, or advanced financial analytics
Demonstrated track record in statistical modeling, forecasting, and business translation
Lead development and enhancement of analytical and behavioral modeling capabilities to power bank-wide forecasting of customer/account analytics, behavioral modeling, statistical forecasting, and model validation.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

sqlpython

Platform: oracle-cloud
Effort: medium