Join us at the forefront of payments innovation, where your expertise in machine learning and generative AI will help shape how money moves worldwide. You will collaborate with diverse teams to deliver impactful solutions, advancing your career in a dynamic and fast-evolving environment. We value your creativity, technical skills, and drive to make a measurable difference. At JPMorganChase, you’ll find opportunities for growth, learning, and meaningful contribution. Together, we’re building the future of payments.
As an Associate Machine Learning Data Scientist in Payments Machine Learning, you will design, develop, and deploy machine learning applications—including generative AI—on cloud infrastructure. You will contribute across the project lifecycle, partnering with senior engineers and data scientists to ensure solutions are reliable, secure, and observable in production. You will communicate progress and results to stakeholders, maintain clear documentation, and help drive innovation in payments and banking operations.
Job Responsibilities:
- Deliver machine learning and AI solutions for payments and banking operations, from discovery to production rollout
- Apply agentic engineering practices to build LLM-powered workflows and evaluate their quality, safety, and reliability
- Contribute to deployment workflows including containerization, CI/CD, automated testing, versioning, monitoring, and rollback procedures
- Develop scalable and secure ML/LLM services integrated with strategic platforms and downstream consumers
- Partner with product, operations, risk and control, and technology teams to clarify requirements and deliver data-led improvements
- Build reusable components such as feature engineering pipelines, evaluation harnesses, and orchestration patterns
- Participate in code and design reviews; contribute to best practices, documentation, and team standards
- Communicate with technical and non-technical stakeholders, translating model outputs into practical decisions
- Maintain documentation such as model cards, runbooks, experiment notes, and operational procedures
Required Qualifications, Capabilities, and Skills:
- Relevant industry experience in applied machine learning, data science, ML engineering, or related roles
- Bachelor’s or Master’s degree in a quantitative field or equivalent practical experience
- Strong understanding of machine learning fundamentals and applied data analysis skills
- Experience designing evaluations and measuring impact in real-world settings
- Experience deploying and operating ML models or ML-enabled services in production, including monitoring and troubleshooting