Risk Management - Data Scientist Associate

Bring your expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about challenging the status quo and striving to be best in class.

As a Data Scientist Associate in our Data Science team, you will explore, pilot, and implement transformative AI solutions-including GenAI-in collaboration with Product, Engineering, and Lines of Business. In this pivotal role, you'll join a team that values experimentation, delivery, and continuous learning, where your ideas are encouraged and operational excellence is a shared goal. You will leverage your expertise in data and advanced analytics to develop robust tools and solutions using the latest AI/ML techniques, cloud technologies, data mesh architectures, and enterprise knowledge bases. Together, we design scalable, high-quality internal solutions that integrate seamlessly into business operations, driving adoption and effective model management. By collaborating with business units, technology partners, and stakeholders, we enable our AI/ML solutions to deliver real business value and become embedded into our workflows for lasting impact., * Apply AI/ML techniques-including LLMs, Generative AI, NLP, and coding assistants-to solve business problems and enhance product capabilities.

• Collaborate with product, business, and cross-functional teams to define project goals, requirements, and plans, participating in stakeholder-facing communications as needed and assist in designing experiments, implementing algorithms, validating results, and productionizing trustworthy, explainable AI/ML solutions.
• Deliver projects using Agile/sprint methodologies, translating business requirements into technical specifications, and supporting milestone achievement.
• Write secure, high-quality production code, review and debug code, and contribute to documentation of code repositories and technical challenges.
• Integrate advanced analytics models and applications into operational workflows to facilitate business value and adoption.
• Implement robust drift monitoring and model retraining processes to maintain accuracy and performance (ongoing performance monitoring).

• Bachelor's or Master's degree in engineering, computer science, statistics, mathematics or a related technical or quantitative field
• Proven track record of deploying, AI, ML, and advanced analytics models in a large-scale enterprise environment.
• Hands-on experience with AI/ML algorithms, statistical modeling, and scalable data processing pipelines.
• Proficiency with machine learning frameworks such as Tensorflow, Pytorch, Scikit-Learn, and agentic workflows and frameworks such as LangChain, LangGraph, and Auto-GPT.
• Ability to convey technical concepts and results to both technical and business audiences.
• Scientific mindset with a proven ability to innovate and work both independently and collaboratively within a team.
• Ability to thrive in a matrixed environment and build effective partnerships with colleagues at various levels and across multiple locations.

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives., Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.