Data scientist role focusing on credit risk modeling and loss forecasting. Collaborating across functions to develop and enhance statistical models for business insights.
Responsibilities
Plan and execute models in the production Reserves and Loss Forecasting process with a focus on CECL
Maintain model data input monitoring, production controls and output analytics including results analysis along with robust documentation of key facets
Support quarterly review process and quarter closing activities, as well as contribute to effective process controls as peer reviewer
Visualize insights, performance, and trends in inputs/outputs for effective communication and decisioning
Drive understanding of drivers and providing narrative support for the assumptions, rationale, and projections to model owners and sponsors
Assist with responding to model validation, regulatory or other oversight requests, including exam findings or issues
Adhere to and follow model governance standards
Support the development of new models or enhancements to existing models
Aid management of models through their lifecycle, from development phase through to implementation into production and outline enhancements for evaluation and future model releases
Meet project timelines, engage in ongoing analysis, find performance thresholds, manage model version control, performance assessments, seek out opportunities for process and model improvements, collaborate on model recalibrations, and re-fits when business dynamics change
Collaborate with other cross functional teams – Forecasting, Reserve and Stress Testing/Capital Management teams, Model Development, Data Governance, Finance, Collections and Controllership
Perform other duties and/or special projects as assigned
Requirements
Bachelor's degree with quantitative underpinning (i.e., Data Science, Computer Science, Risk, Accounting, Business, Economics, Finance, Mathematics, Statistics, Engineering)
3+ years of experience in Programming / Analytics ideally in support of Risk, Credit, Finance, Accounting, Consumer Lending, or other relevant professional and/or educational experience or in lieu of degree 6+ years of experience in Risk, Credit, Finance, Accounting or Consumer Lending
Proven hands-on experience utilizing SQL, Python, Spark, Linux, to perform statistical analysis, query relational databases, and manage large amounts of data
3+ years of experience modeling in areas such as Loss Forecasting, Allowance, Stress Testing, or other areas with consumer credit estimation
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