Applied AI ML Senior Associate

Job summary

Company Chase & Co. (NYSE JPM) is a leading global ficial services firm with operations worldwide. The firm is a leader in investment banking, ficial services for consumers and small business, commercial banking, ficial transaction processing, and asset management. A component of the Dow Jones Industrial Average, Company Chase & Co. serves millions of consumers in the United States and many of the worlds most prominent corporate, institutional and government clients under its Company and Chase brands. Information about Company Chase & Co. is available at Company website.

Chase Consumer & Community Banking (CCB) serves consumers and small businesses with a broad range of ficial services. CCB Risk Management partners with each CCB sub-line of business to identify, assess, prioritize, and remediate risk.

CCB Risk Modeling - Applied AI/ML Senior Associate

• Utilize cutting-edge approaches to design and develop sophisticated machine learning models to drive impactful decisions for the business


• Leverage big data/distributed computing/cloud computing platforms to optimize and accelerate model development processes


• 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 goverce, etc. throughout the entire modeling lifecycle (development, review, deployment, and use of the models)

Basic Qualifications

• Ph. D. or MS degree in Mathematics, Statistics, Computer Science, Operational Research, Econometrics, Physics, or other related quantitative fields


• Deep understanding of advanced machine learning algorithms (e. g. , regressions, XGBoost, Deep Neural Network - CNN, RNN and Transformer, Clustering, Recommendation) as well as design and tuning procedures


• Polished and clear communication

Preferred Qualifications

• 6+ years of experience in developing and managing predictive risk models in ficial industry


• Demonstrated experience in designing, building, and deploying production quality machine learning and deep learning models. Experience in interpreting deep learning models is a plus


• 4+ years of experience and proficiency in coding (Python, Tensorflow or PyTorch, PySpark, SQL), familiarity with cloud services (AWS Sagemaker, Amazon EMR)


• Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency). GPU experience is a plus


• Strong ownership and execution, proven experience in implementing models in production