Principal Risk Data Strategy Lead - AI/ML & Governance

JPMorganChase; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

JPMorgan Chase in New York seeks a Data Strategist Lead in Principal Investment Risk Management to define the risk data strategy and governance model, partnering across lines of business, stakeholders, and technology teams to deliver trusted, decision-grade data products.

You will lead applied AI/ML delivery, spanning generative AI and traditional ML to improve risk oversight, analytics, metrics, and reporting with strong ownership from requirements to scaled adoption.

Qualifications

• Bachelor's degree (or equivalent) in a relevant field or equivalent experience.
• 5+ years in data management, governance, risk analytics, or related domain.
• Strong analytical problem-solving skills in time-sensitive environments.
• Clear writing and verbal communication for stakeholders.
• Foundational knowledge of data management and lifecycle.

Responsibilities

• Own data foundations including sourcing, metadata, lineage, and lifecycle risk controls.
• Define and evolve data governance standards and documentation.
• Deliver risk data products supporting analytics, metrics, and reporting across principal investment process.
• Establish KPIs for quality, timeliness, completeness, and lineage; guide roadmaps.
• Design AI/ML solutions (generative AI, agentic workflows) for risk analytics.
• Implement LLM agents and multi-agent systems including planning and human-in-the-loop escalation.
• Translate business needs into technical designs, acceptance criteria, and execution plans.
• Lead end-to-end delivery from requirements to production and scaled adoption.

Skills

Python

SQL

Data governance

Analytical thinking

Communication

Stakeholder management

Leadership

Education

Bachelor's degree

Tools

Tableau

Job description

JPMorgan Chase in New York seeks a Data Strategist Lead in Principal Investment Risk Management to define the risk data strategy and governance model, partnering across lines of business, stakeholders, and technology teams to deliver trusted, decision-grade data products.

You will lead applied AI/ML delivery, spanning generative AI and traditional ML to improve risk oversight, analytics, metrics, and reporting with strong ownership from requirements to scaled adoption.