JPMorgan Chase & Co.
Risk Management & Compliance - Data Scientist Lead, Executive Director
JPMorgan Chase & Co., Jersey City, New Jersey, United States, 07390
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 solutions—including GenAI—while 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 bases. In 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 (Master’s or Ph.D.) in Data Science, Computer Science, Mathematics, Engineering, or a related field is preferred.
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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 solutions—including GenAI—while 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 bases. In 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 (Master’s or Ph.D.) in Data Science, Computer Science, Mathematics, Engineering, or a related field is preferred.
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