BNY
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VP, AI Change & Portfolio Manager
role at
BNY .
At BNY, our culture empowers us to run our company better and fosters employee growth and success. As a leading global financial services company, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting‑edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
We’re seeking a future team member for the role of VP AI Change & Portfolio Manager to join our Treasury Services team in New York, NY (hybrid). The VP will be the architect of our organization’s AI transformation—guiding end‑to‑end model delivery, driving adoption, and embedding governance to sustain long‑term value.
Responsibilities AI Model Lifecycle Management
Partner with data scientists and engineers to define requirements, develop, test and deploy production‑grade AI/ML models.
Establish MLOps best practices—versioning, CI/CD pipelines, model serving, and automated retraining workflows—to ensure reliability and scalability.
Monitor model performance in production (drift detection, performance metrics) and coordinate remediation or retraining to sustain accuracy and business impact.
Collaborate with IT and Cloud/Ops teams on infrastructure provisioning, security, and compliance for AI workloads.
Adoption and Accountability
Develop multi‑channel communications (roadshows, email campaigns, intranet microsites) to showcase AI solutions and ROI.
Design interactive training programs (workshops, how‑to guides, video tutorials) covering both user‑facing AI tools and the underlying model lifecycle.
Launch targeted adoption campaigns—kickoff workshops, hackathons, “AI Champions” network—and implement scorecards to hold teams accountable for integrating AI into their workflows.
Client & Stakeholder Support
Act as the central coordinator for troubleshooting AI model issues, tuning performance and scaling deployments.
Serve as the go‑to adviser on model interpretability, data requirements, ethical considerations and use‑case feasibility.
Governance & Change Management
Define and operationalize AI governance policies (model risk management, data privacy, bias monitoring) in partnership with Legal, Risk and the AI Hub.
Embed structured change‑control processes—change requests, impact assessments, steering‑committee reviews—to maintain compliance and alignment.
Governance Forum & Portfolio Prioritization
Convene an AI Governance Forum to review, approve and oversee all AI initiative submissions.
Design a standardized proposal template and implement a centralized repository (SharePoint catalog or AI portfolio management tool) to capture initiative metadata.
Develop a consistent scoring model and prioritization rubric based on strategic alignment, business value, technical feasibility, risk profile and compliance impact.
Facilitate quarterly portfolio reviews to evaluate progress, re‑prioritize initiatives, allocate resources and surface governance or change‑management risks.
Communication & Thought Leadership
Translate senior management’s AI vision into clear roadmaps and deliverables; present status updates and impact analyses at leadership forums.
Curate content—use‑case spotlights, metrics dashboards, upcoming milestones—and maintain a dynamic portal for all AI‑related resources.
Material Creation & Training Delivery
Author comprehensive training materials, including best‑practice playbooks on model development and sustaining AI at scale.
Design and lead interactive sessions that walk stakeholders through real‑world model deployment scenarios and operational concerns.
Metrics, KPIs & Reporting
Partner with Finance and Analytics to set measurable targets for model adoption, uptime, performance improvement and cost savings.
Build and maintain reporting tools to track AI portfolio health and surface insights to senior leadership.
Qualifications
5+ years in change management, portfolio leadership or program management—plus 3+ years of hands‑on experience building, deploying and maintaining AI/ML solutions in production.
Deep understanding of AI model development and MLOps practices (CI/CD for ML, model versioning, orchestration tools such as Kubeflow, MLflow, or equivalent).
Strong programming skills (Python, R or similar) and familiarity with cloud platforms (AWS, Azure, GCP) for AI workloads.
Demonstrated ability to establish governance frameworks around AI ethics, model risk and data privacy.
Exceptional communication and presentation skills—comfortable translating technical concepts for business audiences.
Proven track record designing and delivering training curricula and managing digital learning platforms (SharePoint, LMS).
Analytical mindset with experience defining, tracking and reporting on KPIs to drive accountability.
Collaborative approach, able to work across data science, engineering, operations and business functions.
Benefits BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay‑for‑performance philosophy. Flexible global resources and tools support your life’s journey—focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team.
BNY is an Equal Employment Opportunity/Affirmative Action Employer – Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.
#J-18808-Ljbffr
VP, AI Change & Portfolio Manager
role at
BNY .
At BNY, our culture empowers us to run our company better and fosters employee growth and success. As a leading global financial services company, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting‑edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
We’re seeking a future team member for the role of VP AI Change & Portfolio Manager to join our Treasury Services team in New York, NY (hybrid). The VP will be the architect of our organization’s AI transformation—guiding end‑to‑end model delivery, driving adoption, and embedding governance to sustain long‑term value.
Responsibilities AI Model Lifecycle Management
Partner with data scientists and engineers to define requirements, develop, test and deploy production‑grade AI/ML models.
Establish MLOps best practices—versioning, CI/CD pipelines, model serving, and automated retraining workflows—to ensure reliability and scalability.
Monitor model performance in production (drift detection, performance metrics) and coordinate remediation or retraining to sustain accuracy and business impact.
Collaborate with IT and Cloud/Ops teams on infrastructure provisioning, security, and compliance for AI workloads.
Adoption and Accountability
Develop multi‑channel communications (roadshows, email campaigns, intranet microsites) to showcase AI solutions and ROI.
Design interactive training programs (workshops, how‑to guides, video tutorials) covering both user‑facing AI tools and the underlying model lifecycle.
Launch targeted adoption campaigns—kickoff workshops, hackathons, “AI Champions” network—and implement scorecards to hold teams accountable for integrating AI into their workflows.
Client & Stakeholder Support
Act as the central coordinator for troubleshooting AI model issues, tuning performance and scaling deployments.
Serve as the go‑to adviser on model interpretability, data requirements, ethical considerations and use‑case feasibility.
Governance & Change Management
Define and operationalize AI governance policies (model risk management, data privacy, bias monitoring) in partnership with Legal, Risk and the AI Hub.
Embed structured change‑control processes—change requests, impact assessments, steering‑committee reviews—to maintain compliance and alignment.
Governance Forum & Portfolio Prioritization
Convene an AI Governance Forum to review, approve and oversee all AI initiative submissions.
Design a standardized proposal template and implement a centralized repository (SharePoint catalog or AI portfolio management tool) to capture initiative metadata.
Develop a consistent scoring model and prioritization rubric based on strategic alignment, business value, technical feasibility, risk profile and compliance impact.
Facilitate quarterly portfolio reviews to evaluate progress, re‑prioritize initiatives, allocate resources and surface governance or change‑management risks.
Communication & Thought Leadership
Translate senior management’s AI vision into clear roadmaps and deliverables; present status updates and impact analyses at leadership forums.
Curate content—use‑case spotlights, metrics dashboards, upcoming milestones—and maintain a dynamic portal for all AI‑related resources.
Material Creation & Training Delivery
Author comprehensive training materials, including best‑practice playbooks on model development and sustaining AI at scale.
Design and lead interactive sessions that walk stakeholders through real‑world model deployment scenarios and operational concerns.
Metrics, KPIs & Reporting
Partner with Finance and Analytics to set measurable targets for model adoption, uptime, performance improvement and cost savings.
Build and maintain reporting tools to track AI portfolio health and surface insights to senior leadership.
Qualifications
5+ years in change management, portfolio leadership or program management—plus 3+ years of hands‑on experience building, deploying and maintaining AI/ML solutions in production.
Deep understanding of AI model development and MLOps practices (CI/CD for ML, model versioning, orchestration tools such as Kubeflow, MLflow, or equivalent).
Strong programming skills (Python, R or similar) and familiarity with cloud platforms (AWS, Azure, GCP) for AI workloads.
Demonstrated ability to establish governance frameworks around AI ethics, model risk and data privacy.
Exceptional communication and presentation skills—comfortable translating technical concepts for business audiences.
Proven track record designing and delivering training curricula and managing digital learning platforms (SharePoint, LMS).
Analytical mindset with experience defining, tracking and reporting on KPIs to drive accountability.
Collaborative approach, able to work across data science, engineering, operations and business functions.
Benefits BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay‑for‑performance philosophy. Flexible global resources and tools support your life’s journey—focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team.
BNY is an Equal Employment Opportunity/Affirmative Action Employer – Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.
#J-18808-Ljbffr