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 Bank's 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
