BNY Mellon
Overview
At BNY, our culture allows us to run our company better and enables employees' growth and success. We are a leading global financial services company at the heart of the global financial system, influencing a large share of investible assets. We harness AI and breakthrough technologies to collaborate with clients and drive transformative solutions that redefine industries and uplift communities worldwide. We are seeking a future team member for the role of VP AI Change & Portfolio Manager to join our Treasury Services team. This role is located in New York, NY - hybrid. 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 Building Awareness: Develop multi-channel communications to showcase AI solutions and ROI. Empowering Through Education: Design interactive training programs covering user-facing AI tools and the model lifecycle. Driving Adoption: Launch adoption campaigns and implement scorecards to hold teams accountable for integrating AI into workflows. Client & Stakeholder Support On-going Support: Act as the central coordinator for troubleshooting AI model issues, tuning performance and scaling deployments. Ad Hoc Expertise: Serve as the go-to adviser on model interpretability, data requirements, ethical considerations and use-case feasibility. Governance & Change Management Governance Framework: Define and operationalize AI governance policies in partnership with Legal, Risk and the AI Hub. Change Advocacy: Embed structured change-control processes to maintain compliance and alignment. Governance Forum & Portfolio Prioritization Establish an AI Governance Forum: Convene a cross-functional steering committee to review, approve and oversee AI initiative submissions. Intake Process & Central Repository: Design a standardized proposal template and implement a centralized repository to capture initiative metadata. Prioritization Methodology: Develop a scoring model and rubric based on strategic alignment, business value, feasibility, risk and compliance impact. Quarterly Portfolio Reviews: Facilitate meetings to evaluate progress, re-prioritize initiatives and surface governance or change-management risks. Communication & Thought Leadership Executive Liaison: Translate AI vision into roadmaps and deliverables; present status updates and impact analyses at leadership forums. Fortnightly Newsletter & SharePoint: Curate content and maintain a portal for AI resources. Material Creation & Training Delivery Content Development: Author training materials, including best-practice playbooks on model development and scaling AI. Workshops & Webinars: Design and lead sessions that cover real-world model deployment scenarios and operational concerns. Metrics, KPIs & Reporting Define Success Metrics: Set measurable targets for model adoption, uptime, performance improvement and cost savings. Dashboards & Scorecards: Build and maintain reporting tools to track AI portfolio health and surface insights to senior leadership. Qualifications
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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. Company Information & Diversity
BNY is an Equal Employment Opportunity/Affirmative Action Employer. We value diverse perspectives and backgrounds. Compensation & Benefits
BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. The base salary for this position is estimated between $81,000 and $130,000 per year, with final figures determined on experience and location, and may include additional incentive opportunities. This position is at-will and the Company reserves the right to modify base salary or other compensation at any time. Our benefits include generous paid leave, volunteer time, and resources to support health, resilience and financial goals.
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At BNY, our culture allows us to run our company better and enables employees' growth and success. We are a leading global financial services company at the heart of the global financial system, influencing a large share of investible assets. We harness AI and breakthrough technologies to collaborate with clients and drive transformative solutions that redefine industries and uplift communities worldwide. We are seeking a future team member for the role of VP AI Change & Portfolio Manager to join our Treasury Services team. This role is located in New York, NY - hybrid. 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 Building Awareness: Develop multi-channel communications to showcase AI solutions and ROI. Empowering Through Education: Design interactive training programs covering user-facing AI tools and the model lifecycle. Driving Adoption: Launch adoption campaigns and implement scorecards to hold teams accountable for integrating AI into workflows. Client & Stakeholder Support On-going Support: Act as the central coordinator for troubleshooting AI model issues, tuning performance and scaling deployments. Ad Hoc Expertise: Serve as the go-to adviser on model interpretability, data requirements, ethical considerations and use-case feasibility. Governance & Change Management Governance Framework: Define and operationalize AI governance policies in partnership with Legal, Risk and the AI Hub. Change Advocacy: Embed structured change-control processes to maintain compliance and alignment. Governance Forum & Portfolio Prioritization Establish an AI Governance Forum: Convene a cross-functional steering committee to review, approve and oversee AI initiative submissions. Intake Process & Central Repository: Design a standardized proposal template and implement a centralized repository to capture initiative metadata. Prioritization Methodology: Develop a scoring model and rubric based on strategic alignment, business value, feasibility, risk and compliance impact. Quarterly Portfolio Reviews: Facilitate meetings to evaluate progress, re-prioritize initiatives and surface governance or change-management risks. Communication & Thought Leadership Executive Liaison: Translate AI vision into roadmaps and deliverables; present status updates and impact analyses at leadership forums. Fortnightly Newsletter & SharePoint: Curate content and maintain a portal for AI resources. Material Creation & Training Delivery Content Development: Author training materials, including best-practice playbooks on model development and scaling AI. Workshops & Webinars: Design and lead sessions that cover real-world model deployment scenarios and operational concerns. Metrics, KPIs & Reporting Define Success Metrics: Set measurable targets for model adoption, uptime, performance improvement and cost savings. Dashboards & Scorecards: 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. Company Information & Diversity
BNY is an Equal Employment Opportunity/Affirmative Action Employer. We value diverse perspectives and backgrounds. Compensation & Benefits
BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. The base salary for this position is estimated between $81,000 and $130,000 per year, with final figures determined on experience and location, and may include additional incentive opportunities. This position is at-will and the Company reserves the right to modify base salary or other compensation at any time. Our benefits include generous paid leave, volunteer time, and resources to support health, resilience and financial goals.
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