Applied AI ML Lead - Global Banking

We have an exciting and rewarding opportunity for you to take your Predictive Science career to the next level.

As an Applied AI ML Lead - Data Scientist- Vice President at JPMorgan Chase within the Commercial & Investment Banks Global Banking team, you ll leverage your technical expertise and leadership abilities to support AI innovation. You should have deep knowledge of AI/ML and effective leadership to inspire the team, align cross-functional stakeholders, engage senior leadership, and drive business results.

Job Responsibilities

• Lead a local AI/ML team with accountability and engagement into a global organization.
• Mentor and guide team members, fostering an inclusive culture with a growth mindset.
• Collaborate on setting the technical vision and executing strategic roadmaps to drive AI innovation.
• Deliver AI/ML projects through our ML development life cycle using Agile methodology, help transform business requirements into AI/ML specifications, define milestones and ensure timely delivery.
• Work with product and business teams to define goals and roadmaps, maintain alignment with cross-functional stakeholders.
• Exercise sound technical judgment, anticipate bottlenecks, escalate effectively, and balance business needs versus technical constraints.
• Design experiments, establish mathematical intuitions, implement algorithms, execute test cases, validate results and productionize highly performant, scalable, trustworthy and often explainable solution.
• Mentor junior team members in delivering successful projects and building successful career in the firm.
• Participate and contribute back to firmwide Machine Learning communities through patenting, publications and speaking engagements.
• Evaluate and design effective processes and systems to facilitate communication, improve execution and ensure accountability.

Required qualifications, capabilities, and skills

• Formal training or certification on Predictive Science concepts and 5+ years applied experience
• Track record of managing AI/ML or software development teams and experience as a hands-on practitioner developing production AI/ML solutions.
• Deep expertise in machine learning and artificial intelligence, with a proven ability to enable teams to deliver high-quality solutions rapidly . Highly skilled in designing robust metrics, formulating data-driven hypotheses, and driving measurable business outcomes through strategic application of advanced analytics.
• Extensive experience in multiple cutting-edge fields such as AI Agents, Gen-AI (Prompt Engineering including RAG), Large Language Models, Natural Language Processing, Knowledge Graphs, Reinforcement Learning, Ranking, and Recommendation Systems, with proven ability to bridge research and practical implementation.
• Solid foundation in data structures, algorithms, and statistics, complemented by hands-on experience in monitoring machine learning and large language models (LLMs), ensuring model explainability, and managing end-to-end deployment and inferencing in production environments.
• Demonstrated proficiency with leading machine learning frameworks, including TensorFlow, PyTorch & MXNet.
• Advanced programming skills in Python and Spark, with strong experience in vectorized operations (NumPy, SciPy) and distributed computing (multithreading, multi-GPU, Dask, Ray, Polars).
• Familiarity with agentic workflows and relevant frameworks such as LangChain, LangGraph, Autogen, CrewAI and Auto-GPT.
• Familiarity in DataBricks, AWS Cloud services such as AWS Connect, EMR, Sagemaker etc.
• Strong people management, team-building skills and ability to coach and grow talent, foster a healthy engineering culture and attract/retain talent, build a diverse, inclusive, and high-performing team.
• Ability to inspire collaboration among teams composed of both technical and non-technical members, effective communication, solid negotiation skills, and strong leadership.

Preferred qualifications, capabilities, and skills

• 14+ years (BE/BTech/BS) or 8+ (ME/M. Tech/MS) or 5+ (PhD) years of relevant experience in Computer Science, Information Systems, Statistics, Mathematics, or equivalent experience.
• Experience working at code level