Applied AIML Data Scientist Lead - Vice President

Job Description

The Legal Applied AI/ML team in Corporate Technology at JPMorgan Chase focuses on solving challenging business problems such as semantic search, question answering, document analysis, and automation of service inquiries using data science and machine learning techniques, particularly GenAI and LLM tools and techniques. The role involves working with the firm’s rich internal and external data pool using GenAI frameworks, Python/Spark via AWS, and other systems. Proficiency in deriving business insights from technical results and presenting them to non‑technical audiences is required.

As an Applied AI/ML Data Scientist Lead‑Vice President on the Corporate team, you will study complex business problems and apply advanced algorithms to develop, test, and evaluate AI/ML applications or models for those problems.

Job Responsibilities

• Work closely with product managers, data scientists, ML engineers, and other stakeholders to understand requirements and prioritize use cases.
• Develop GenAI and LLM solutions to solve business problems.
• Implement optimization strategies to fine‑tune generative models for specific GenAI use cases, ensuring high‑quality outputs.
• Execute tasks throughout the model development process, including data wrangling/analysis, model training, testing, and selection.
• Generate structured and meaningful insights from data analysis and modelling exercises and present them in an appropriate format for the audience.
• Communicate AI/GenAI capabilities and results to both technical and non‑technical audiences.
• Stay informed about the latest trends and advancements in AI research, implement cutting‑edge techniques, and leverage external APIs for enhanced functionality.

Required Qualifications, Capabilities, and Skills

• PhD in Computer Science or a related quantitative discipline with 2+ years of relevant experience, or MS/BS in Computer Science or a related field with 4+ years of relevant experience.
• Practical experience with LLM projects and other supervised/unsupervised techniques; a proven track record of deploying AI/ML applications in production.
• Proficient programming skills with Python and SQL, as well as practical experience with other languages such as R, Java, or equivalent.
• Demonstrated experience working with large and complex datasets.
• Experience with ML frameworks, libraries, and APIs such as TensorFlow, PyTorch, Scikit‑learn, and OpenAI API.
• Experience integrating user feedback to establish agentic refinement and self‑improving AI applications.
• Solid understanding of fundamentals of statistics and machine learning (classification, regression, time series, deep learning, reinforcement learning) and generative model architectures, particularly Transformers.
• Ability to identify and address AI/LLM challenges, implement optimizations, and tune models for optimal performance in NLP applications.
• Excellent problem‑solving, communication (verbal and written), and teamwork skills.

Preferred Qualifications, Capabilities, and Skills

• Experience working with engineering teams to operationalize ML models.
• Expertise in designing and implementing pipelines using RAG and Agentic AI framework.
• Hands‑on knowledge of Chain‑of‑Thoughts, Tree‑of‑Thoughts, and Graph‑of‑Thoughts prompting strategies.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans.