Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in our team to partner with the Business to provide a comprehensive view.

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  

Develop and maintain a comprehensive library of predictive variables to enhance the consistency and quality of data used in machine learning models across the customer lifecycle, including acquisition, account management, transaction authorization, and collections.Collaborate closely with senior management to leverage cutting-edge machine learning techniques, developing innovative attributes and modeling solutions, and successfully deploying them into production.Innovate and design new attributes using creative approaches for Credit Risk Models. Conduct research to evaluate the effectiveness and accuracy of new data sources and collection methods, ensuring optimal incorporation on new information in models. Oversee attribute quality testing and monitoring by employing modern techniques to identify data and attribute issues, recognize patterns, and enhance attribute accuracy and consistency, while establishing effective warning systems and tools.Partner with teams across Marketing, Risk, Technology, Data Governance, and Control to support the entire lifecycle of attribute development and modeling.

Required qualifications, capabilities, and skills

Advanced degree in Mathematics, Statistics, Computer Science, Operations Research, Econometrics, Physics, or a related quantitative field.Minimum 3 years of experience working with large datasets, including developing or managing the development and implementation of attributes and predictive models.Proficiency in programming languages such as Python, TensorFlow, PyTorch, PySpark, and SQL, along with familiarity with cloud services like AWS SageMaker and Amazon EMR.A fundamental understanding of the consumer lending business and its dynamics.Strong ability to analyze, interpret, and derive insights from data.Advanced problem-solving and analytical skills, with a keen attention to detail.Excellent communication skills, with the ability to convey complex information clearly and effectively to senior management.

Preferred qualifications, capabilities, and skills

Strong understanding of advanced statistical methods and machine learning techniques, including GLM/Regression, Random Forest, Boosting, Decision Trees, Neural Networks, Clustering, KNN, Anomaly Detection, Simulation, Scenario Analysis etc.Proven experience in designing, building, and deploying production-quality machine learning models.Familiarity with the U.S. market lending business and/or credit card industry.Ability to effectively collaborate with multiple stakeholders on projects of strategic importance, ensuring alignment and successful outcomes.