You are a strategic, future-focused data and artificial intelligence leader who is passionate about re-imagining Operations through scalable, trusted, and intelligent platforms. You have found the right team.
As a Data and Artificial Intelligence Lead within the Unity Product team in Markets Operations Transformation, you will help shape and deliver the data, analytics, and intelligence foundation for Unity, JPMorganChase’s artificial intelligence-first Operations platform for Corporate and Investment Bank Operations.
You will lead the design of trusted operational data models, intelligent automation capabilities, and executive insights that allow the firm to measure automation, strengthen controls, reduce operational risk, and identify the next set of opportunities at scale. You will combine hands-on data leadership, applied artificial intelligence delivery, and product thinking to build capabilities that are reliable, auditable, and ready for the future of agent-led workflows.
Job Responsibilities
- Define and deliver Unity’s operational data architecture, including event-level lineage, transition-level data capture, and end-to-end process journey modeling
- Establish data models, keys, relationships, and controls across complex operational workflows where multiple inputs may lead to a single outcome
- Own cloud-based data platform design, including retention strategy, reproducible backfills, large-scale query performance, and cost-aware architecture
- Lead the strategy and delivery of classification, enrichment, routing, and intelligent automation models that improve operational outcomes
- Build feedback loops that compare artificial intelligence outputs with final human-approved outcomes to improve accuracy, quality, and value realization
- Shape the roadmap from assistive intelligence to governed autonomous workflows, including confidence scoring, drift detection, escalation handling, and risk controls
- Define trusted metric frameworks for automation, resolution time, service levels, escalation, and operational performance across business lines
- Deliver insight capabilities that turn operational data into foresight, helping identify future automation, risk, workload, and efficiency opportunities
- Enable self-service analytics for business users through scalable semantic layers, business intelligence tools, and reusable data products
- Champion data governance, lineage, quality, auditability, and explainability across all data and artificial intelligence-driven decisions
- Partner with product teams, operations leaders, technology, risk, and control stakeholders to deliver scalable and trusted capabilities across the firm
Required Qualifications, Capabilities, and Skills
- 10+ years of experience in data engineering, data architecture, applied artificial intelligence, or machine learning
- 3+ years of experience leading data, analytics, artificial intelligence, or machine learning teams, platforms, or large-scale initiatives
- Hands-on experience with modern cloud data platforms, Amazon Web Services, including Athena, Glue, Iceberg, and S3 or equivalent technologies
- Strong expertise in large-scale structured query language, event-based data, streaming concepts, dimensional modeling, and operational data design
- Proven experience delivering production-grade artificial intelligence or machine learning models, including classification, natural language processing, monitoring, and retraining
- Experience defining metric frameworks, data products, and insight layers from ambiguous business requirements
- Strong understanding of data governance, lineage, quality, controls, and audit requirements in a regulated environment
- Ability to design for enterprise scale, cost efficiency, reliability, and long-term platform reuse
- Experience working with senior stakeholders across operations, product, technology, risk, and control functions
- Excellent communication skills, with the ability to translate complex data and intelligence concepts into clear business outcomes
- Strong product mindset with the ability to build reusable, modular capabilities rather than one-off solutions
Preferred Qualifications, Capabilities, and Skills
- Experience in financial services, capital markets, markets operations, workflow platforms, case management, or exception management
- Experience designing human-in-the-loop artificial intelligence systems and governed autonomous or agent-led workflows
- Familiarity with business intelligence, semantic layers, and self-service analytics tools such as Qlik Sense or equivalent platforms
- Experience building feedback loops that measurably improve model quality, automation performance, and operational outcomes over time
- Exposure to large language model applications, generative artificial intelligence, or multi-agent architectures in enterprise environments
- Demonstrated ability to design predictive insights for workload, risk, breach, escalation, or operational trend detection
- Experience building trusted data foundations for executive reporting, auditability, and cross-business performance measurement