CCB_Data and Analytics

CCB-Risk- Card Data Science & Capabilities Associate

JP Morgan Chase

Our Firmwide Risk Function

Chase Consumer & Community Banking

Model Insights Team

Job Responsibilities

• Drive synergy in model performance tracking across different sub-lines of business.


• Enhance model performance framework to holistically capture model health, providing actionable insights to model users.


• Collaborate with model developers to identify potential opportunities for model calibration and conduct preliminary Root Cause Analysis in case of model performance decay.


• Design and build robust framework to monitor quality of model inputs.


• Explore opportunities to drive efficiency in model inputs and performance tracking through use of Large Language Model (LLM).


• Partner with teams across, Risk, Technology, Data Governance, and Control to support effective model performance management and insights.


• Deliver regular updates on model health to senior leadership of risk organization and the first line of defense.

Required qualifications, capabilities, and skills

• Advanced degree in Mathematics, Statistics, Computer Science, Operations Research, Econometrics, Physics, or a related quantitative field.


• Proficiency in programming languages such as Python, PySpark, and SQL, along with familiarity with cloud services like AWS SageMaker and Amazon EMR.


• Deep understanding of advanced machine learning algorithms (e. g. Decision Trees, Random Forest, XGBoost, Neural Networks, Clustering etc)


• Strong conceptual understanding of performance metrics used to monitor health of machine learning models.


• Fundamental understanding of the consumer lending business and risk management practices.


• Experience of working with large datasets with 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

• 3+ years of experience in developing and managing predictive risk models in financial industry.


• Experience of data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency).


• Proven expertise in designing, building, and deploying production-quality machine learning models.


• Ability to effectively collaborate with multiple stakeholders on projects of strategic importance, ensuring alignment and successful outcomes.


• Basic level of proficiency in Tableau

CCB-Risk- Card Data Science & Capabilities Associate

JP Morgan Chase

Our Firmwide Risk Function

Chase Consumer & Community Banking

Model Insights Team

Job Responsibilities

• Drive synergy in model performance tracking across different sub-lines of business.


• Enhance model performance framework to holistically capture model health, providing actionable insights to model users.


• Collaborate with model developers to identify potential opportunities for model calibration and conduct preliminary Root Cause Analysis in case of model performance decay.


• Design and build robust framework to monitor quality of model inputs.


• Explore opportunities to drive efficiency in model inputs and performance tracking through use of Large Language Model (LLM).


• Partner with teams across, Risk, Technology, Data Governance, and Control to support effective model performance management and insights.


• Deliver regular updates on model health to senior leadership of risk organization and the first line of defense.

Required qualifications, capabilities, and skills

• Advanced degree in Mathematics, Statistics, Computer Science, Operations Research, Econometrics, Physics, or a related quantitative field.


• Proficiency in programming languages such as Python, PySpark, and SQL, along with familiarity with cloud services like AWS SageMaker and Amazon EMR.


• Deep understanding of advanced machine learning algorithms (e. g. Decision Trees, Random Forest, XGBoost, Neural Networks, Clustering etc)


• Strong conceptual understanding of performance metrics used to monitor health of machine learning models.


• Fundamental understanding of the consumer lending business and risk management practices.


• Experience of working with large datasets with 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

• 3+ years of experience in developing and managing predictive risk models in financial industry.


• Experience of data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency).


• Proven expertise in designing, building, and deploying production-quality machine learning models.


• Ability to effectively collaborate with multiple stakeholders on projects of strategic importance, ensuring alignment and successful outcomes.


• Basic level of proficiency in Tableau