Join JPMorgan Chase and help shape the future of AI-driven innovation in financial services.

As Lead Applied AI ML - Data Scientist within the Commercial & Investment Bank's 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 applied machine learning team and collaborate across a global organization to deliver high‑impact outcomes.
• Define technical vision, shape strategic roadmaps, and align stakeholders across product, business, and technology.
• Translate business requirements into machine learning specifications, milestones, and agile delivery plans.
• Design experiments, implement algorithms, validate results, and productionize scalable, trustworthy, and explainable solutions.
• Refine model capabilities using Py Torch and scikit‑learn; apply causal inference with Do Why to quantify treatment effects and inform experimental decisions.
• Utilize Hugging Face Transformers and Lang Chain to explore counterfactual reasoning in large language models; produce research materials, internal notes, and demos that enable stakeholder adoption.
• Build and operate model development and operations workflows for training, deployment, monitoring, and continuous improvement.
• Exercise sound technical judgment, anticipate bottlenecks, and balance business needs with technical constraints.
• Mentor and coach team members, foster an inclusive culture, and grow talent.
• Contribute to firmwide machine learning communities through publications, talks, patents, and knowledge sharing.
• Evaluate and improve processes that enhance execution, communication, and accountability.

Required qualifications, capabilities, and skills

• Masters with 7+ years experience or PhD with 3+ years of experience in Computer Science, Information Systems, Statistics, Mathematics, or equivalent experience.
• Track record of managing AI/ML or software development teams.
• Experience as a hands-on practitioner developing production AI/ML solutions.
• Knowledge and experience in machine learning and artificial intelligence. Ability to set teams up for success in speed and quality, and design effective metrics and hypotheses.
• Expert in at least one of the following areas: Large Language Models, Natural Language Processing, Knowledge Graph, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.
• Good understanding of Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics.
• Must have good knowledge on agentic patterns and relevant frameworks, such as Lang Chain, Lang Graph, Auto-GPT etc.
• Strong understanding of AI implementation in software development and legacy code transformation.
• Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, AI evaluation, RAG (Similarity Search).
• Demonstrated expertise in machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn.
• Programming knowledge of python, spark; Strong grasp on vector operations using numpy, scipy etc

Preferred qualifications, capabilities and skills

• Familiarity in AWS Cloud services such as EMR, Sagemaker etc.,
• Strong people management and team-building skills. Ability to coach and grow talent, foster a healthy engineering culture, and attract/retain talent. Ability to 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.