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As a Risk Modeling - Machine Learning Associate within our Consumer and Community Banking Risk Modeling team, you will be responsible for the development and implementation of machine learning models, statistical models, segmentations, and strategies. You will have the opportunity to utilize big data and distributed computing platforms, applying them to risk management for our consumer and small business portfolio. The ICB (International Consumer Bank) business within JPMorgan has grown significantly since its launch in 2021, and we expect the business to expand further over the next few years. Join the expansion of the Chase digital bank across the UK and Europe and help us continue to build our award-winning bank.In this role you will be responsible for development of models and  will be able to  build a solid understanding of various consumer products and key risk drivers for statistical credit models of those products and ensure that we are able to synergize use of vendor models.
You will also have an opportunity to use your experience with econometric/statistical modeling, data manipulation, query efficiency techniques, reporting and automation.

Job Responsibilities:

• Evaluate, test, and validate vendor models for their effectiveness to address the business proposition being evaluated (typically credit risk) as well as other risk components.
• Understand/evaluate efficiency of state-of-the-art modeling techniques including both classical statistical modeling approaches and modern machine learning approaches to enhance existing models and tackle challenging modeling problems.
• Manage end-to-end model development process, including data sourcing, manipulation, exploratory data analysis and pattern discovery, documentation, assisting with implementation, and performance monitoring.
• Collaborate with cross functional partners in Risk, Finance, Technology, Model Governance throughout the entire modeling life cycle.
• Interact with third party vendors and making sure Chase can gain maximum synergies on use of these vendor models.

Required qualifications, capabilities, and skills

• Minimum 3 to 9 yrs of relevant experience
• Advanced degree in a quantitative discipline (e.g., Mathematics, Statistics, Economics, Computer Science, Operations Research) with 3 to 9 years of relevant working experience
• Strong data analysis and statistical/economic modeling experience, such as generalized linear models, multivariate analysis, and time series analysis.
• Proficiency in advanced analytical languages (e.g., SAS, Python, R); 
• Ability to work with large data and perform extensive analysis to draw useful insights.
• Strong communication skills to present to and collaborate with business partners and model end-users. 
• Strong organizational and multi-tasking skills with demonstrated ability to manage expectations and deliver quality results on time.
• Comfortable working both independently and in a team environment.

Preferred qualifications, capabilities, and skills

• Knowledge of vendor management/ similar experience in past is very useful
•  Doctoral degree is preferred.
• Familiarity with framework of machine learning pipeline (e.g., tensor flow, scikit-learn) is not required but a plus.