JPMorgan CCB Risk Program Associate 

United States, Delaware, Wilmington 

579283142

Job Responsibilities-

• Design and develop machine learning models to drive impactful decisions for the card business throughout the customer lifecycle (e.g., acquisition, account management, transaction authorization, collection).
• Research, develop, document, implement, maintain, and support tools and frameworks for AI/ML model explainability and fairness.
• Utilize cutting-edge machine learning approaches and construct sophisticated machine learning models including deep learning architectures on big data platforms.
• Work closely with the senior management team to develop ambitious, innovative modeling solutions and deliver them into production.
• Collaborate with various partners in marketing, risk, technology, model governance, research etc. throughout the entire modeling lifecycle (development, review, deployment, and use of the models)

Required qualification, capabilities and skills-

• Ph.D. or Master’s degree from an accredited university in a quantitative field such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering
• Demonstrated experience in designing, building, and deploying production quality machine learning models.
• Deep understanding of advanced machine learning algorithms (e.g., regressions, XGBoost, Deep Neural Network – CNN and RNN, Clustering, Recommendation) as well as design and tuning.
• Experience in interpreting machine learning models such as XGBoost, GBM, etc. Experience in interpreting deep learning models is a plus.
• At least one year of experience and proficiency in coding (e.g., Python, Tensorflow, Spark, or Scala) and big data technologies (e.g., Hadoop, Teradata, AWS cloud, Hive) .

Preferred qualification, capabilities and skills

• Strong expertise, interest, and track record of performing cutting-edge research on Explainable AI
• Experience in credit card industry with strong business acumen.
• Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency). GPU experience is desired.
• Strong ownership and execution; proven experience in implementing models in production