Risk Management & Compliance Data Scientist Lead, Executive Director

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 an Executive Director Data Scientist in Risk Management & Compliance you will have the opportunity to shape how we leverage artificial intelligence and advanced analytics to solve complex business challenges. You will guide us in exploring piloting and implementing transformative AI solutionsincluding GenAIwhile collaborating closely with Product Engineering and Lines of Business. Together we will foster a culture of experimentation delivery and continuous learning encouraging new ideas and maintaining operational excellence.

You will help build and mentor a high-performing team focused on deep data understanding and advanced analytics driving the development of robust tools and solutions using cutting-edge AI/ML techniques cloud technologies and enterprise knowledge this strategic and hands-on role you will engage with technical aspects review code monitor the impact of production GenAI models and enable rapid prototyping ensuring our solutions deliver real business value and are seamlessly integrated into our operations.

Job Responsibilities

• Oversee and manage a global team of data scientists who are responsible for the development of predictive models autonomous agents and prompt-based LLM solutions in collaboration with Engineering teams.
• Manage the end-to-end model development lifecycle including planning execution continuous improvement risk management and ensuring solutions are scalable and aligned with business objectives.
• Collaborate with senior leaders to re-engineer processes and define a compelling vision for the target state by embedding AI into current workflows driving change and efficiency.
• Design build and deploy impactful AI and data-driven applications using cloud data mesh and knowledge base technologies such as centralized repositories semantic search and automated information retrieval systems that organize store and provide easy access to critical business data and insights.
• Integrate advanced analytics models and applications into operational workflows to ensure business value and adoption.
• Guide research initiatives and pilot projects to identify and apply cutting-edge AI/ML solutions including GenAI and agentic technologies.
• Implement robust drift monitoring and model retraining processes to maintain accuracy and performance (ongoing performance monitoring).
• Prepare and deliver executive-level presentations and reports communicating analytical findings and recommendations to senior leadership.

Required Qualifications Capabilities and Skills

• Minimum 10 years of experience in data science analytics or a related field.
• Proven track record of deploying operationalizing and managing AI ML and advanced analytics models in a large-scale enterprise environment including hands-on experience with ML Ops frameworks tools and best practices for model monitoring automation and lifecycle management.
• Significant leadership experience in managing data science/R&D teams and driving technology innovation.
• Extensive experience in AI/ML algorithms statistical modeling and scalable data processing pipelines with a strong background in modern data platforms (e.g. Snowflake Databricks) cloud-based technologies data mesh architectures and big data ecosystems.
• Experience with A/B experimentation data- and metric-driven product development cloud-native deployment in large-scale distributed environments and the ability to develop and debug production-quality code.
• Strong written and verbal communication skills with the ability to convey technical concepts and results to both technical and business audiences.
• Scientific mindset with the ability to innovate and work both independently and collaboratively within a team.
• Ability to thrive in a matrix environment and build partnerships with colleagues at various levels and across multiple locations.
• Proven experience in agentic frameworks (using CruxAI Google ADK LangGraph).

Preferred Qualifications Capabilities and Skills:

• Advanced degree (Masters or Ph.D.) in Data Science Computer Science Mathematics Engineering or a related field is preferred.