Vista previa generada por IA
Vice President, Data Transfer – Integration & Quality leadership role in London.
Drive AI strategy, roadmap, governance and responsible AI across BNY’s Financing Platform.
We’re seeking a future team member for the role of Vice President Data Transfer - Integration & Quality to join our Markets – Securities Finance team . This role is located in London.
In this role, you’ll make an impact in the following ways:
- Define an AI vision and multi‑year roadmap for the Financing Platform, tightly aligned to platform OKRs and BNY’s strategic pillars (Be More for our Clients, Run our Company Better, Power our Culture).
- Build and manage an AI use‑case portfolio: assess value, feasibility, data readiness, and risk; prioritize for outcomes and time‑to‑value.
- Lead discovery and delivery: drive problem framing, experimentation, MVPs, and scaling of solutions in production; implement robust measurement plans (adoption, ROI, quality, risk).
- Navigate governance and controls: shepherd initiatives through BNY’s AI governance processes (e.g., ADAB approvals, MRMG requirements, Permit to Build/Operate, Ongoing Performance Monitoring); ensure documentation, testing, and monitoring are in place.
- Partner across platform teams: collaborate with engineering on model serving and performance, with data teams on feature pipelines, and with product on client impact and rollout.
- Champion Responsible AI: ensure privacy, fairness, explainability, and model risk controls are embedded in design and operations.
- Drive change management: prepare stakeholders for adoption; deliver training and enablement; capture feedback to iterate solutions.
- Track and report outcomes: establish KPIs and OKRs; report progress to platform leadership; support quarterly planning and budget discussions.
To be successful in this role, we’re seeking the following:
- Demonstrated success defining AI strategy, building roadmaps, and leading cross‑functional delivery from MVP to scale with measurable impact.
- Hands‑on familiarity with modern ML/GenAI stacks (Python, model lifecycle, ML Ops/CI‑CD, cloud services, data pipelines, monitoring/observability).
- Ability to translate business problems into technical plans and explain technical concepts to non‑technical audiences.
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field;