
Risk Management & Compliance - Data Scientist Lead, Executive Director
at J.P. Morgan
Posted 16 days ago
No clicks
Senior data science leader in Risk Management & Compliance responsible for building and mentoring a global team to design, deploy, and operate AI/ML and GenAI solutions. The role oversees end-to-end model development and production lifecycle, including monitoring, drift detection, and MLOps best practices. You'll collaborate with Product, Engineering and business leaders to embed AI into workflows, drive pilots and scaleable implementations, and present findings to senior leadership. Hands-on involvement in architecture, code review, cloud/data platform integration, and agentic/LLM-based solutions is required.
- Compensation
- Not specified
- City
- Jersey City
- Country
- United States
Currency: Not specified
Full Job Description
Location: Jersey City, NJ, United States
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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