Join the Global Private Bank Transformative AI organization at JPMorgan Chase, where we are revolutionizing how the Bank services and advises clients, driving process transformation, deepen client engagements and generate revenue for the firm. As a Data Scientist, you will spearhead cutting-edge Language Modelling projects that will redefine the Wealth Management business into a PB Agentic Bank. Your role will focus on mining extensive data related to client interactions, market trends, investment strategies and existing processes, recommending transformative solutions through autonomous agents. This is a unique opportunity to collaborate with a world-class team of Data Scientists and Machine Learning Engineers, making a significant impact on the firm's business and technology processes. At JPMorgan, you'll be part of a premier analytics community committed to skill development and career growth in analytics, data science, machine learning, and beyond.

 

Job Responsibilities:

Develop innovative insights by understanding business dynamics and underlying data, applying intelligence to transform existing processes for enhanced efficiency and faster client request fulfillment.Become a data expert across the Global Private Bank, creatively transforming data into actionable insights.Identify strategic machine learning use cases, applying techniques such as data analytics, summarization, clustering, statistical analysis, question answering, time-series prediction, customer lifecycle management, and recommendation systems.Collaborate with cross-functional teams, including Advisors, Investment Specialists, Client Service, Operations, Product Management, and Technology, to design autonomous agentic solutions that enhance business efficiency and generate additional revenue.Communicate technical concepts effectively to both technical and non-technical stakeholders.Build and maintain data pipelines and processing workflows for prompt engineering on LLMs.Analyze and interpret data to evaluate model performance and identify areas for improvement.

Required Qualifications, Capabilities, and Skills:

Master’s degree in a data science-related discipline with at least seven years of banking industry experience, or a PhD with at least three years of industry experience.Extensive experience in data analysis and transformation, particularly using Python.Strong communication skills to convey technical concepts and results to both technical and business audiences.Thorough knowledge of deep learning concepts, including attention mechanisms, transformers, and language modeling.Experience in data pre-processing, feature engineering, and data analysis.Excellent problem-solving skills, with the ability to communicate ideas and results clearly to stakeholders and leadership.Ability to thrive in a fast-paced environment, managing multiple projects simultaneously.Scientific thinking with the ability to innovate and work both independently and collaboratively.Curious, hardworking, detail-oriented, and motivated by complex analytical challenges.

Preferred Qualifications, Capabilities, and Skills:

Strong knowledge of the financial services industry, particularly in Private and Retail Banking.Experience working with SQL and NoSQL databases, handling large datasets.Experience with A/B testing and data/metric-driven product development.Industry experience in implementing machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, Scikit-Learn, Keras).