Provide data analytics to the Mortgage, Consumer and Deposit lines of business, evaluating credit risk across the full lifecycle of our products.
Primary focus areas include portfolio, scenario, and strategic analysis, portfolio acquisitions and divestitures, and ad-hoc Executive analytics.
Other focus areas include marketing campaign response, evaluating success of strategic initiatives, account acquisition and management, delinquency and default, and overall portfolio asset quality.
Utilize internal and external data to drive decision-making and identify opportunities. Monitor trends in the industry. Focus on getting the most out of data and exploring new areas of analysis.
You will be part of the decision and data science function: including contributing to the development of underwriting models, customer segmentation methodologies, marketing targeting, attribution and response models, as well as the evaluation of new data sources and performing advanced data processing
You will carry out data processing and analysis including statistical analysis, variable selection, dimensionality reduction, custom attribute engineering,
You will help with the design, development, evaluation and monitoring of predictive models and advanced algorithms that help the business to drive decisions throughout the customer lifecycle (prospecting, acquisition, underwriting, fraud, collections, ).
You will leverage methods from diverse disciplines such as machine learning, statistical modelling, information theory, information retrieval and other areas to gain customer insights, draw conclusions and work with business partners to put those insights into
You will work closely with business partners, technology and customer analytics teams to evaluate new and alternate data sources as well as computing paradigms and analytical
You will participate in data architecture decisions and partner with technology teams to implement models/algorithms in production
You will be part of a growing and exciting team and will help document your assumptions, methodologies, as well as carry out validation and testing to facilitate peer reviews and independent model validation
Master’s degree in quantitative areas like Applied Math, Statistics, Engineering, Computer Science or related