Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. In this role, you’ll apply strong technical judgment to choose the right approaches (including modern LLM-based methods where appropriate), evaluate performance with rigorous metrics, and ensure solutions are reliable, secure, and scalable in real-world environments. You’ll also contribute to improving data quality and feedback loops, monitoring models in production, and continuously iterating to reduce agent effort, shorten resolution times, and increase consistency and quality across operational workflows.
As an Applied AI/ML Senior Associate in our AI for Operations organization, you will help design, build, and scale cutting-edge Natural Language Processing (NLP) solutions that improve experiences for both customers and internal agents supporting the bank’s day-to-day operations. You’ll work hands-on across the end-to-end model lifecycle—partnering with product, engineering, operations, and risk stakeholders to translate real operational needs into production-grade language capabilities such as intelligent search, summarization, classification, and next-best-action recommendations.
Job Responsibilities:
- Oversee the analysis of complex datasets to inform decisions on real-world applications.
- Lead the development and implementation of models and algorithms to enhance existing systems, processes, and products.
- Supervise data analysis activities and ensure effective visualizations are provided.
- Ensure the writing and deployment of software code in production systems is efficient and meets standards.
- Anticipate risks associated with machine learning solutions and prediction/classification systems and strategize mitigation.
- Communicate complex issues clearly and credibly to senior management and stakeholders.
- Foster a transparent cross-functional work environment and influence peers and team members to uphold these standards.
Required qualifications, capabilities and skills:
- Master's degree in computer Science, Machine Learning, or a related field with 3+ years experience OR Ph.D in computer Science, Machine Learning, or a related field with 1+ year of experience.
- Expertise in one or more of the following areas: machine learning, Graph learning, recommendation systems, network analysis, natural language processing, Reinforcement learning, MLOps, Gen AI, LLMs.
- Solid understanding of core CS concepts, including common data structures and algorithms.
Preferred qualifications, capabilities and skills:
- Experienced in conducting design and code reviews.
- Proficient in cloud environments such as AWS, GCP, or Azure.
- Experienced in managing and deriving insights from large, both unstructured and structured datasets.