As a Lead Data Scientist with the Chief Data Office, you’ll help shape the future of the Chief Administrative Office and its businesses by applying world-class machine learning expertise. You’ll collaborate on a wide array of product and business problems with cross-functional partners across Finance, Supplier Services, Data Security, Global Real Estate, and Customer Experience. You’ll use data and analysis to identify and solve our division’s biggest challenges and develop state-of-the-art GenAI and LLM models to solve real-world problems. By joining JP Morgan Chief Data Office (CAO), you’ll be part of a world-class data science community dedicated to problem solving and career growth in ML/AI and beyond.

Job Summary 

Lead hands-on development and technical direction for GenAI, LLM, and agentic AI solutions.Collaborate with cross-functional teams to deliver scalable, production-ready AI systems.Drive adoption of modern ML infrastructure and best practices.Communicate technical concepts and results to both technical and business stakeholders.Ensure responsible AI practices and model governance.

Job Responsibilities 

Master’s or PhD in Computer Science, Engineering, Mathematics, or a related quantitative field.10+ years of hands-on experience in applied machine learning, including GenAI, LLMs, or foundation models.Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX).Proven experience designing, training, and deploying large-scale ML/AI models in production environments.Deep understanding of prompt engineering, agentic workflows, and orchestration frameworks.Experience with cloud platforms (AWS, Azure, GCP) and distributed systems (Kubernetes, Ray, Slurm).Solid grasp of MLOps tools and practices (MLflow, model monitoring, CI/CD for ML).Ability to communicate complex technical concepts to both technical and business stakeholders

Preferred Qualifications

Experience with high-performance computing and GPU infrastructure (NVIDIA DCGM, Triton Inference).Familiarity with big data processing tools and cloud data services.Background in financial services or regulated industries.Published research or contributions to open-source GenAI/LLM projects.