Data Scientist Senior Associate (AI/ML) - Risk Management

Put your data science and AI expertise to work on challenges that strengthen a global firm and create real-world impact. You will help design and deliver transformative AI and advanced analytics solutions that can be adopted at scale. You will collaborate closely with Product, Engineering, and business partners in a team that values experimentation, delivery, and continuous learning. If you enjoy turning ideas into resilient products and improving how models perform over time, this role offers meaningful growth and visibility.

As an Associate, Data Science in the Data Science team within Risk Management and Compliance, you will explore, pilot, and implement impactful AI solutions in partnership with Product, Engineering, and lines of business. You will help build scalable internal tools that integrate into business operations and support effective model management. You will contribute to a culture of experimentation and operational excellence where your ideas are encouraged. You will collaborate with stakeholders to ensure solutions deliver measurable value and become embedded into workflows for lasting impact.

Job Responsibilities

• Design and implement explainable AI/ML solutions and multi-agent systems, including orchestration layers that coordinate specialized agents, manage task routing, and integrate human-in-the-loop controls
• Develop production-grade solutions by writing secure, maintainable code, performing code reviews, debugging issues, and contributing to clear technical documentation (design notes, runbooks, and repository documentation)
• Collaborate with data science peers, product partners, business stakeholders, and cross-functional teams to define project goals and requirements and participate in stakeholder-facing communications
• Partner with Model Risk and Compliance stakeholders to ensure AI/ML solutions adhere to firmwide Responsible AI standards, including model documentation, bias and fairness testing, and appropriate human-in-the-loop controls
• Deliver projects using Agile and sprint methodologies by translating business requirements into technical specifications and supporting milestone achievement
• Integrate solutions into operational workflows by collaborating with engineering teams on APIs and batch pipelines, deployment patterns, reliability, and user adoption
• Implement drift monitoring and model retraining processes to maintain model accuracy and performance through ongoing performance monitoring

Required Qualifications, Capabilities, and Skills

• Demonstrated experience in data science, analytics, or a related field
• Demonstrated experience deploying, operationalizing, and managing AI, ML, or advanced analytics models in a large-scale enterprise environment
• Working knowledge of AI/ML algorithms, statistical modeling, and scalable data processing pipelines
• Proficiency with Python-based machine learning libraries such as TensorFlow, PyTorch, and scikit-learn
• Familiarity with orchestration frameworks (for example, LangGraph) and agent design patterns
• Strong written and verbal communication skills with the ability to explain technical concepts and results to technical and non-technical audiences
• Demonstrated ability to innovate, work independently, and collaborate effectively within a team environment
• Demonstrated ability to succeed in a matrix environment and build partnerships across levels, functions, and locations

Preferred Qualifications, Capabilities, and Skills

• Bachelor’s or Master’s degree in engineering, computer science, statistics, mathematics, or a related quantitative field
  

About Risk Management and Compliance

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