Vice President, AI program Lead

BNY Mellon•Pittsburgh, PA

1d•$69,000 - $146,000

About The Position

As an AI Program Lead at BNY, you will lead a cross-functional team focused on identifying, developing, deploying, and scaling AI-driven solutions that address business needs and improve operational efficiency. You will act as the primary point of leadership for the POD, guiding strategy, execution, and delivery while ensuring alignment with BNY’s enterprise AI priorities, governance standards, and risk framework. In this role, you will bridge business needs with artificial intelligence, analytics, and operational transformation capabilities. You will partner closely with AI Hub, data scientists, engineers, Ops Hub, platform teams, and business stakeholders to shape AI opportunities, prioritize use cases, and deliver practical, responsible AI applications. You will also provide day-to-day leadership to POD team members, fostering collaboration, innovation, and continuous improvement.

Requirements

Bachelor’s degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field.
Prior experience in AI/ML, analytics, data science, or a related technical discipline.
Demonstrated experience leading projects, workstreams, or teams in a cross-functional environment.
Experience working with business stakeholders to translate strategic priorities into practical technology or analytics solutions.

Responsibilities

Lead the identification and prioritization of business processes where AI/ML, analytics, and automation can deliver measurable value.
Oversee the end-to-end development, validation, deployment, and monitoring of AI and machine learning solutions.
Guide the team in data preparation, feature engineering, exploratory analysis, and solution design to support effective modeling efforts.
Ensure AI solutions are scalable, practical, and aligned to business objectives, operational needs, and enterprise architecture standards.
Monitor solution performance post-deployment and drive continuous improvement opportunities.
Lead, coach, and develop POD team members, creating a high-performing team environment focused on delivery, innovation, and accountability.
Set clear priorities, assign work across the POD, and ensure effective execution against timelines and business commitments.
Serve as the primary escalation point for delivery, resource, and execution issues within the POD.
Foster collaboration across business, operations, and technology stakeholders to remove blockers and maintain momentum.
Provide mentorship to team members on AI/ML practices, business analysis, and stakeholder engagement.
Partner with product owners, AI Hub, Ops Hub, platform teams, and business units to define requirements and ensure AI solutions achieve intended business outcomes.
Translate complex technical concepts into clear, actionable insights for non-technical stakeholders and senior leadership.
Work closely with data engineering and technology teams to integrate AI solutions into scalable production workflows.
Facilitate alignment between stakeholders on objectives, scope, risks, dependencies, and success measures for AI initiatives.
Ensure POD activities adhere to responsible and ethical AI practices in line with enterprise governance frameworks.
Oversee testing, validation, and documentation to support model accuracy, fairness, transparency, and compliance.
Partner with control, risk, and compliance stakeholders to ensure AI solutions meet applicable standards and review requirements.
Promote disciplined delivery practices that balance innovation with strong risk management and control execution.
Stay current with emerging AI trends, tools, and techniques, and assess their relevance to business opportunities within the POD.
Drive research into new methodologies and present recommendations to enhance internal AI capabilities.
Champion adoption of AI solutions by helping stakeholders understand business value, change impacts, and implementation considerations.
Contribute to the broader AI community within BNY by sharing insights, best practices, and lessons learned across teams.