Finance AI Data Strategy Manager

Accenture•Miami, FL

4d•$80,400 - $293,800•Hybrid

About The Position

Our Finance AI and Data Strategy practitioners work to create and execute an organization’s business strategy for Finance AI and Data transformation including: defining a compelling industry & Finance function vision, creating value & ROI models, architecting a client’s Finance AI talent strategy, ecosystem partnership approaches, creating scalable operating capabilities, and envisioning best-in-class business/technology architecture & roadmaps. Use scaled agile disciplines to transform a client’s business and Finance function by sequencing the delivery of critical data elements, data products and feature functionality. This isn't a role where you maintain the status quo. You'll work at the cutting edge of Finance transformation — helping the world's largest organizations reimagine what's possible when AI and data are built into the core of how Finance operates. You'll shape strategy at the C-suite level, build lasting client relationships, and leave engagements knowing you moved something that mattered. If you want scope, influence, and the chance to define what AI-led Finance looks like for an entire industry, this is it.

Requirements

5+ years of deep fluency in AI & Data Strategy — from enterprise-wide data architecture to function-specific plays across Finance, HR, and Operations. You've shaped the thinking, not just executed it.
5+ years of focused Finance AI and Data work — you understand how CFO organizations operate, what keeps Finance leaders up at night, and how AI and data can change that calculus.
5+ years developing value cases and ROI models — you can translate a bold vision into a business case that gets funded and a roadmap that gets built.
5+ years of hands-on data management and analysis, paired with the strategic instinct to know which insights actually matter to the C-suite.
5+ years conducting client assessments and requirements gathering — you know the right questions to ask, and you listen for what's not being said.
2+ years applying Responsible AI principles in live engagements — you build trust into your work, not as an afterthought, but as a differentiator.
5+ years of leading workstreams end-to-end across complex, multi-stakeholder environments — you're the person others look to when deadlines matter and the pressure is real.
5+ years of large-scale global delivery — you've navigated time zones, cultures, and matrix organizations, and you know what it takes to keep distributed teams aligned.
5+ years working directly with corporate and/or business unit Finance processes, functions, and systems — you can speak the language fluently, not just translate it.
Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)

Nice To Haves

You've led. You build effective teams, foster inclusive environments, and are known for strong client relationships that outlast the engagement.
You've originated. You're entrepreneurial — you know how to spot an opportunity, shape a deal, and bring it across the finish line.
You're a clear communicator. Strong written and verbal communication; you can adapt your message for a CFO, a data engineer, and a board room in the same week.
You keep learning. You bring innovative thinking to every project and actively seek out new ideas, tools, and approaches.
You have a Master's degree in a relevant field

Responsibilities

Shape the vision. Define compelling Finance AI strategies that connect to real business outcomes — revenue upside, cost takeout, and competitive advantage.
Earn the room. Build trusted advisor relationships with CFOs and senior Finance leaders, becoming their go-to thought partner on AI and data transformation.
Architect the path forward. Design AI and data strategies that cover technology platforms, data foundations, operating models, and talent — not just the technology layer.
Make the case. Develop the business case, investment profile, and ROI models that turn a bold vision into a funded, sequenced roadmap.
Assess and diagnose. Evaluate an organization's AI and data maturity across strategy, talent, operating model, and data infrastructure — and know exactly what needs to change.
Build for scale. Use scaled agile disciplines to sequence delivery of critical data elements, data products, and feature functionality that compound over time.
Embed Responsible AI. Infuse ethical AI principles from the start — building client trust and making responsibility a competitive differentiator, not a compliance checkbox.
Drive commercialization. Identify and develop AI-first product strategies and ecosystem partnerships that open new revenue streams for clients.