VP, Quality Assurance & AI-Driven Process Excellence

Morgan Stanley; Columbus (OH); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Morgan Stanley is seeking a Quality Assurance Manager to lead the Quality program across Morgan Stanley and E*TRADE channels, defining scalable sampling, governance, and inspection standards. This role partners with SRU leadership and Field Services to drive metrics, risk mitigation, and continuous improvement in a high-volume, time-sensitive environment.

The role emphasizes building a standardized QA framework, calibrating processes, and leveraging analytics to identify trends and root causes,

Qualifications

• 10+ years of financial services experience in operations, risk/controls, or related functions.
• 5+ years of people leadership across multiple sites.
• Ability to lead large-scale process improvement programs.

Responsibilities

• Define enterprise-quality strategy and scalable sampling framework across SRU, Field Services, Home Office, and other lines of business.
• Oversee daily quality oversight, trend analytics, and risk mitigation with executive reporting.
• Drive closed-loop quality improvements through calibration, coaching, and training partnerships.
• Lead multi-site teams with strong morale and accountability in a fast-paced environment.
• Champion AI-enabled efficiency initiatives and standardized sampling across the organization.

Skills

Leadership

Quality Oversight

Analytics

Governance

Calibration

AI/Automation Awareness

Stakeholder Management

Project Management

Education

Bachelor's degree

Advanced degree preferred

Tools

Tableau

Power BI

SQL

Python

SAS

Job description

Morgan Stanley is seeking a Quality Assurance Manager to lead the Quality program across Morgan Stanley and E*TRADE channels, defining scalable sampling, governance, and inspection standards. This role partners with SRU leadership and Field Services to drive metrics, risk mitigation, and continuous improvement in a high-volume, time-sensitive environment.

The role emphasizes building a standardized QA framework, calibrating processes, and leveraging analytics to identify trends and root causes,