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Vice President, Strategy Lead
lead · Consulting
We’re seeking a future team member for the role of Vice President, Enterprise AI Strategy to join our Enterprise AI team. This role is located in New York City.
In this role, you’ll make an impact in the following ways:
- Own strategic planning for AI and data initiatives: translate enterprise priorities into a multi-quarter AI strategy, roadmap, and investment plan; define portfolio governance and decision cadence.
- Lead business case development and value realization: build and review ROI scenarios, benefits hypotheses, capacity plans, and operating impacts; ensure initiatives have measurable KPIs/OKRs and adoption plans.
- Frame and prioritize AI use cases: partner with business and product leaders to identify high-impact opportunities; evaluate feasibility, risk, and scalability; drive clear go/no-go recommendations.
- Influence operating model and change management: define roles, processes, and ways of working required to scale AI solutions; drive stakeholder alignment and adoption across business lines.
- Provide executive storytelling: develop crisp narratives for senior forums, including strategy updates, performance reporting, and decision memos that simplify complex technical concepts.
To be successful in this role, we’re seeking the following:
- Bachelor’s degree required; MBA or Master’s degree preferred (Strategy, Business, Analytics, Computer Science, or related fields).
- Typically 6-10+ years of experience in strategy consulting, corporate strategy, transformation, product strategy, or analytics/AI strategy within large enterprises (financial services a plus).
- Demonstrated ability to lead ambiguous, cross-functional workstreams and deliver outcomes through influence (not just direct authority).
- Strong analytical and commercial acumen: structured problem solving, financial modeling concepts, and prioritization frameworks.
- Exceptional written and verbal communication skills with proven ability to communicate to executive audiences.
Working familiarity with AI/ML concepts (including GenAI), model lifecycle basics, and the practical realities of deploying solutions in regulated environments.