Vice President - Screening Efficiency & Analytics Strategy Lead

Join us at Chase and make a real impact every day for your customers, your community, and yourself.

Build your career on our strong foundation and help shape what's next-for you and for us.

We value creativity, growth, and collaboration, offering opportunities to advance your skills and career.

Be part of a team that transforms data into decisions and solutions for a global leader in financial services.

As a Vice President - Screening Service Efficiency & Analytics Strategy Lead within JPMorgan Chase, you will lead the transformation of how sanctions screening performance is measured, analyzed, and improved-shifting the organization from reactive reporting to predictive, actionable insights that reduce false positives, improve performance, optimize end-to-end operational efficiency, and accelerate automation opportunities across the sanctions screening infrastructure and workflow.

You will serve as a bridge between analytics/technology teams and operations, compliance, and governance forums, translating complex data into clear "brutal truth" narratives and decision-ready executive reporting.

Job Responsibilities


* Develop and maintain an enterprise metrics framework for sanctions screening, including KPI scorecards and leading/lagging indicators, with clear definitions, sources, and reporting cadence.


* Establish governance standards for metric definitions, data lineage, assumptions, and auditability; maintain documentation to support reviews/exams and change management controls.

Lead recurring stakeholder forums to present insights, drive decisions, and track benefits realization from tuning, process changes, and automation.


* Analyze alert/case/disposition/investigation data to identify and quantify drivers of false positives (e.g., name commonality, geography, list updates, transliteration patterns, and data quality issues).


* Produce recurring trend and root-cause analyses on volumes, hit/true match rates, aging/throughput, and backlog drivers; segment performance by scenario/filter, list source, business/product, jurisdiction, and customer/entity attributes.

Deliver data-driven tuning recommendations (e.g., threshold adjustments, token/alias handling, matching logic refinements, and data standardization), including pre/post measurement and regression monitoring.


* Define, monitor, and evolve filter/service KPIs (e.g., alert-to-customer ratio, override rates, repeat-alert rates, list refresh impact, etc)


* Perform structured performance reviews after watchlist updates, ruleset releases, parameter changes, and vendor upgrades; build monitoring to detect drift, sudden spikes, or unusual match patterns and trigger investigations/corrective actions.


* Map the end-to-end sanctions workflow and use data to identify bottlenecks, rework, duplicate effort, and queue imbalance; generate insights on cycle times, handoffs, productivity, and quality outcomes (e.g., reopen rates, QA outcomes, escalation patterns).
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