Head of Programme Management

Key Responsibilities:
Own and manage the end-to-end monthly production cycle for the AI disruption monitoring workstream — from data collection coordination through final report delivery
Serve as the primary point of coordination across cross-LOB data owners, domain subject matter experts, and internal partners, ensuring timely inputs and feedback at each stage of the cycle
Draft and produce regular written updates, briefs, and executive summaries that distill complex analytical findings into clear, concise narratives for senior audiences
Coordinate and facilitate SME check-ins across pillar areas (customer/digital, competitive intelligence, workforce/HR, risk/compliance), preparing agendas, capturing notes, and extracting key signals
Work closely with the Data Scientist to understand analytical outputs, flag inconsistencies or gaps, and ensure the narrative accurately reflects the underlying data
Manage stakeholder communications, timelines, and deliverable tracking to keep the workstream on schedule and unblock dependencies
Leverage AI and GenAI tools to drive efficiency across coordination, note synthesis, first-draft writing, and report distribution — and proactively identify opportunities to automate repetitive tasks
Help build and refine the processes, templates, and workflows that will define how this capability operates at steady state
Maintain and organize the workstream's knowledge base, data source inventory, and stakeholder map
Stay current on the rapidly evolving AI economy landscape — proactively identifying key sources of information, tracking emerging developments, and surfacing relevant signals to the team

Required Qualifications, Capabilities and Skills:
Bachelor's degree with approximately 5 years of relevant professional experience in program management, strategy, consulting, analytics, or a related field
Strong written communication skills — demonstrated ability to produce clear, polished deliverables that translate complex or technical material for non-technical audiences
Proven ability to manage multi-stakeholder processes with competing timelines and drive them to completion independently
Organizational rigor — comfort managing multiple parallel workstreams, tracking dependencies, and keeping a production cycle on schedule
Demonstrated familiarity with the AI and GenAI landscape — including awareness of key players, market dynamics, and emerging trends. You should be someone who already follows this space and can identify credible sources of information independently
Demonstrated early adoption of AI and technology tools in a professional context — you don't need to be a developer, but you should be someone who gravitates toward new tools and figures them out quickly
Intellectual curiosity and willingness to develop working familiarity with data platforms, analytical outputs, and technical concepts
Ability to navigate a matrixed organization and build productive working relationships across teams with different priorities
Comfort with ambiguity — this is a new capability being built from scratch, and the processes you manage will evolve as we learn

Preferred Qualifications, Capabilities and Skills:
Experience in financial services, economic research, consulting, or technology strategy
Familiarity with data visualization tools (Tableau, Power BI) or light technical skills (SQL, Python basics)
Experience working with or alongside data science teams
Experience building new programs, processes, or operational capabilities from the ground up