Vice President, POM Product Management
Indexed description
Key Responsibilities
SLA Strategy, Governance & Operating Model
- Define and maintain the end‑to‑end SLA framework, including metrics, prioritization logic, risk exposure drivers, and data quality requirements.
- Embed SLA rules into operational workflows and Staff Workstation, ensuring they become a core driver for prioritization, exception management, and escalation
- Own the intake and triage of all client change submissions, ensuring each request is appropriately classified and routed for assessment.
- Coordinate Impact Assessments (IAs) by aligning with technology, operations, legal, and domain stakeholders to define scope, timelines, dependencies, cost, and contractual implications.
- Ensure SLA‑compliant turnaround, particularly for accelerated or regulatory changes, escalating risks that may affect service performance or deadlines.
- Facilitate governance routines between internal teams and the client to support prioritization, clarify requirements, and remove blockers.
- Communicate proactively with client counterparts and BNY leadership on progress, risks, decisions, and timelines across the change lifecycle.
- Provide executive leadership to SLA‑focused PODs, engineers, and analysts toward measurable outcomes.
- Drive adoption of best‑in‑class product practices, including OKR‑aligned execution, initiative definition, and cross‑POD coordination.
- Foster a culture of transparency, continuous improvement, and proactive client‑service excellence.
- Extensive experience in custody operations, data delivery, or large‑scale financial services platforms, ideally with deep knowledge of SLA‑driven environments.
- Proven track record in Product Development or equivalent, with strong leadership, communication, and stakeholder‑influencing skills.
- Demonstrated expertise in data management, operational workflows, risk monitoring, and reporting frameworks.
- Ability to navigate complex cross‑platform dependencies and drive outcomes through pods in an Agile operating model.
- Strong analytical mindset with ability to interpret data signals, operational metrics, and client needs to drive decision‑making.
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