About this role
Lead data science initiatives in JPMorgan Chase & Co.’s Global Services Insights & Analytics team within Commercial Banking. The role focuses on reliable, scalable and governed generative AI and large language model (LLM) solutions that improve planning, efficiency, service and controls across financial-services use cases. The position is listed in Chicago, Illinois, and Plano, Texas.
Responsibilities
- Develop LLM applications for content extraction, enterprise and semantic search, question answering, reasoning, summarization and recommendations. Design prompt-based and retrieval-augmented generation systems, including tool use, structured outputs and multi-step agentic workflows.
- Prototype and deploy applications with Amazon Bedrock; use Cortex, including Cortex Analyst, for governed analytics and AI-assisted workflows. Partner with engineering and product teams on scalable APIs, batch jobs and services, and maintain structured and unstructured data pipelines for preprocessing, indexing and retrieval.
- Build evaluation frameworks covering accuracy, faithfulness, robustness, latency and cost, with red-teaming and safety checks where applicable. Apply research on prompting, fine-tuning, evaluation and agent design; establish operational readiness, mentor junior data scientists and promote responsible AI practices.
- Translate business needs into measurable problems, solution designs and success metrics, and communicate tradeoffs, risks and results to technical and non-technical stakeholders.
Required qualifications
- An advanced degree in Data Science, Computer Science, Machine Learning, Statistics or a related quantitative field, or equivalent practical experience; 5+ years of applied machine learning or NLP experience, including production deployment.
- Experience with LLMs, prompt engineering, retrieval-augmented generation, evaluation, Amazon Bedrock or an equivalent managed LLM platform, and enterprise Cortex workflows. Strong Python skills; familiarity with PyTorch or TensorFlow and tools such as pandas, NumPy and scikit-learn.
- Experience with APIs, application integration, data pipelines, embeddings, vector search and retrieval; software engineering practices including version control, testing and CI/CD. Strong analytical, communication and stakeholder-management skills, plus working knowledge of financial services, markets or asset management.
Preferred
Deeper knowledge of LLM agents, planning and reasoning; MLOps practices such as experiment tracking, model registries, monitoring and rollback; and cloud deployment, preferably AWS, including containers or orchestration platforms.
Applicants must be authorized to work in the United States; the employer does not provide employment-based immigration sponsorship or assistance with OPT or CPT. Listed base pay is $128,250–$200,000 for either location. Eligible roles may receive incentive compensation and benefits, subject to eligibility.