- Python mandatory. Nonrisk modeling and predictive analytics

- Designing and building the model management framework including model generation of periodic performance metrics to assess fitness for purpose of a variety of industry-leading Statistical, Econometric, and Artificial Intelligence / Machine Learning models to solve a variety of business problems  ranging from Marketing Analytics to the management of Deposit and non-Deposit portfolios

Examples of model applications include:

- Predicting how households and businesses respond to changing interest rates and economic conditions

- Building spatial models to optimize the coverage of Chase's branch network

- Developing machine learning approaches to predict customer behavior

- Performing periodic (monthly/quarterly) generation of identified model performance measures on assigned models (statistical models as well AI/ML-based models)

- Presentation of Model Management reports to senior leadership as well as business and / or operational teams; helping the team and the organization analyze and interpret model performance results and draw actionable insights from the same

- Supporting the entire Model Governance Lifecycle end-to-end: on-board new models, modify details on existing models, retire old models, flag any model governance issues to Controllers as well as leadership

- Providing thought leadership and technical/SME inputs to build a Digital Model Management platform

- Streamlining and/or automation of existing Model Management codes for select models as well as streamlining and/or automation of input data accesses

Role and Responsibilities:

- Manage Working hands-on (~70% of effort) plus mentoring and coaching other resources/juniors/analysts/interns on the team to ensure seamless project delivery (~30% of effort) for the entire Model Management team

- While formal people management responsibilities will not be there initially there is a need to streamline the team as it grows significantly; we are looking for someone senior who can bring in domain, technical, project and stakeholder management skills to support the Team Lead in end to end project delivery and team management

- Working hands-on with a variety of programming languages (SAS, R, Python, etc.) as well as dealing with large and complex datasets (including some in Big Data environments)

- Communicating (written as well as verbal) quantitative concepts and results to a range of (technical and non-technical) audiences across the business, including senior leaders

- Collaborating with team members to improve and automate processes

Qualifications:

- The candidate should have a Masters (or Ph.D.) in a quantitative field of study with a solid foundation in two or more of the following areas:

- Statistical and Econometric Theory Linear and non-Linear models

- Time Series and Longitudinal Data Analysis

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