Vice President, Data Scientist Lead

As a Data Scientist in Consumer and Community Banking’s Data & Analytics team, you’ll play a pivotal role in shaping JPMC’s AI strategy, y ou’ll enable a new paradigm of analysis and insights by helping make our extensive data assets AI-ready. Your expertise in Natural Language Processing (NLP), Artificial Intelligence (AI), and Machine Learning (ML) will be key to building innovative tools to enhance metadata quality and delivering actionable insights.

You will collaborate closely with product and technology teams, creatively translating complex business challenges into scalable, data-driven solutions. Join a collaborative and thoughtful team where your problem-solving skills will drive data discoverability and strengthen governance across the organization.

• Leverage statistical tools, machine learning, and generative AI to modernize data at scale
• Apply NLP methods to analyze and extract information from large, diverse datasets
• Identify and prototype creative solutions to address user needs and business challenges
• Establish best practices and design pipelines for data validation and quality assurance
• Develop data models and architectures to support metadata management
• Collaborate with product and tech teams to translate business requirements into data-driven and AI-powered solutions

• 5+ years of experience as a data science professional, or equivalent
• Bachelor’s degree in Computer Science, Computational Linguistics, or a related discipline
• Proficiency in ML, NLP, and generative/agentic AI tools and technologies (e.g., "Python", "scikit-learn", "Hugging Face", "OpenAI")
• Excellent communication and collaboration skills, with the ability to convey subject matter expertise and complex AI concepts to non-technical audiences
• Strong organizational skills, including the ability to manage multiple projects, prioritize conflicting deadlines, and adapt to ambiguity

• Master’s degree or PhD in Computer Science, Computational Linguistics, or a related discipline
• Experience with structured data, semantic vocabularies, knowledge graphs, and complex data ecosystems