Risk Management - Data Strategist Lead - Vice President

JPMorgan Chase & Co.; New York; Presencial; USD 140.000 - 190.000; Jornada completa

Descripción de la vacante

JPMorgan Chase & Co. is seeking a Data Strategist Lead in Principal Investment Risk Management to define and execute the risk data strategy and governance model across business lines and technology teams, delivering trusted, decision-grade data products for risk oversight.

You will lead applied AI/ML initiatives, including generative AI and multi-agent workflows, ensuring verification, validation, and guardrails.

Formación

• Bachelor's degree (or equivalent) in a relevant field or equivalent professional experience.
• 5+ years of experience in data management, governance, risk analytics, data science or related domain.
• Strong analytical problem-solving skills with time-sensitive environments.
• Clear written and verbal communication; producing high-quality documentation.
• Foundational knowledge of data management and end-to-end data lifecycle.
• Proficient in Python and SQL.
• Experience building dashboards with Tableau.
• Cross-functional collaboration to define requirements and drive approvals.
• Deliver with accountability from requirements to production.
• Data quality and data protection discipline.

Responsabilidades

• Own principal risk data foundations including sourcing, metadata, lineage, and lifecycle controls.
• Define and evolve data governance standards and self-service patterns.
• Deliver risk data products supporting operations, analytics, and reporting across the investment process.
• Establish measurable data KPIs and steer roadmaps accordingly.
• Design applied AI/ML solutions for risk analytics and oversight.
• Implement LLM agents and multi-agent systems including planning and human-in-the-loop escalation.
• Translate business needs into designs, acceptance criteria, and execution plans.
• Lead end-to-end delivery from requirements to production adoption.
• Build verification/validation mechanisms for safe outputs.
• Operate production solutions with monitoring, drift management, and iteration.
• Partner with technology teams to document data sources and flows for downstream readiness.

Conocimientos

Analytical problem-solving

Communication

Data management principles

Python

SQL

Tableau

Cross-functional collaboration

Delivery ownership

Data quality

Data protection

LLM platform

Agent orchestration

Observability

Data governance tools

Big data platforms

Cloud/DevOps

Automation

Educación

Bachelor's degree

Descripción del empleo

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 thinking outside the box, challenging the status quo and striving to be best-in-class.

Job Summary:

As aData Strategist LeadinPrincipal Investment Risk Management, you will define and execute the risk data strategy and governance model while partnering across lines of business, functional stakeholders, and technology teams to deliver trusted, decision-grade data products.

You will lead applied AI/Machine Learning delivery - spanning generative AI, agentic workflows, and traditional Machine Learning to improve risk oversight, analytics, metrics, and reporting. You will operate with strong ownership from requirements through scaled adoption, ensuring verification, validation, and guardrails that produce safe and reliable outputs in production.

Job Responsibilities:

• OwnPrincipal Risk's data foundations including controlled sourcing/integration, metadata/catalog, lineage, and lifecycle risk controls (protection, retention/destruction, storage, usage, quality).
• Defineand evolve data governance standards, publishing patterns, and documentation expectations to enable trusted consumption and self-service.
• Deliverrisk data products that support business operations, strategic objectives, analytics, metrics, and reporting across the principal investment process.
• Establishmeasurable data KPIs (e.g., quality, timeliness, completeness, lineage coverage, control adherence) and use them to steer roadmap and prioritization.
• Designapplied AI/ML solutions (generative AI, agentic workflows, traditional ML) to address Principal Risk analytics and oversight use cases.
• ImplementLLM agents and multi-agent systems including planning, parallel task execution, entity resolution, and human-in-the-loop escalation.
• Translatebusiness needs into delivery artifacts including technical designs, acceptance criteria, measurable outcomes, and execution plans.
• Leadend-to-end delivery from requirements POC production scaled adoption, including operating model handoff where needed.
• Buildverification and validation mechanisms such as business-rule checks, evaluation datasets, and regression testing to ensure safe and reliable outputs.
• Operateproduction solutions through monitoring, performance/stability improvements, drift management, and continuous iteration.
• Partnerwith technology teams to document data sources, formats, and flows while implementing validation to ensure downstream readiness for analytics and reporting.
  

Required Qualifications, Capabilities, and Skills:

• Bachelor's degree (or equivalent experience) in a relevant field (e.g., data science, computer science, engineering, math, sciences) or equivalent professional experience.
• 5+ years of experience in data management, data governance, risk management/analytics, data science, or a closely related domain.
• Demonstratestrong analytical problem-solving skills with the ability to execute effectively in time-sensitive environments.
• Communicateclearly in writing and verbally, producing high-quality documentation and influencing business, risk, and technology stakeholders.
• Applyfoundational knowledge of data management principles and end-to-end data lifecycle management.
• Programeffectively in Python and work confidently with SQL (or similar querying languages).
• Buildand interpret dashboards/analysis using Tableau (or equivalent BI experience aligned to the role’s needs).
• Collaboratecross-functionally to define requirements, align stakeholders, and drive approvals for delivery and adoption.
• Executedelivery with accountability, including defining outcomes, tracking progress, and managing dependencies through to production.
• Promotestrong data quality and control discipline, including validation and readiness for downstream reporting and analytics.
• Adhereto data protection and usage expectations appropriate for risk data and decisioning workflows.
  

Preferred Qualifications, Capabilities, and Skills:

• Deliverhands-on experience with an LLM platform (model onboarding/serving, prompt/version management, evaluations).
• Buildexperience with agent orchestration frameworks (tool use, retrieval-augmented generation, state/context management).
• Operationalizeproduction systems with observability, alerting dashboards, runbooks, and post-deploy monitoring/continuous improvement.
• Usefamiliarity with data governance tooling for catalog/metadata/lineage and modern data publishing standards.
• Leveragefamiliarity with big data platforms, data architecture patterns, and governance tools/platforms.
• Applycloud/DevOps exposure (e.g., AWS, Linux, Git) and observability tooling experience to support reliable delivery.
• Demonstratea track record of measurable improvements through automation, operational rigor, and end-to-end data lifecycle initiatives (onboarding, integrity checks, archiving, migration/decommissioning).