Senior Director Data and AI Strategy and Advisory

We are seeking a Senior Director to lead our Data and AI Strategy and Advisory sub-practice.
The Head of Data and AI Strategy will work with C-suite and senior business, technology, data, and risk stakeholders to identify strategic opportunities, develop data and AI roadmaps, design operating models, prioritize use cases, build investment cases, and guide organizations through responsible execution at scale. This is a senior leadership role combining client advisory, practice leadership, go-to-market execution, offering development, thought leadership, and delivery oversight.

1. Client Advisory and Executive Leadership

Serve as a trusted advisor to C-suite and senior client stakeholders on data, analytics, generative AI, agentic AI, automation, and broader AI-enabled transformation.
Lead end-to-end Data and AI strategy engagements, including current-state assessment, future-state visioning, roadmap development, business case creation, operating model design, and value realization planning.
Facilitate executive workshops to identify high-value opportunities, align stakeholders, prioritize use cases, and define measurable outcomes.

1. Data and AI Strategy Development

Define AI transformation roadmaps, including high-impact use cases for generative AI, agentic AI, advanced analytics, automation, and data modernization.
Develop prioritization frameworks, investment cases, success metrics, value capture models, and implementation plans.

1. Operating Model, Governance and Transformation Design

Define and embed data and AI operating models, including decision rights, governance forums, roles and responsibilities, delivery models, funding models, and value realization mechanisms.
Help clients establish scalable AI governance frameworks, including responsible AI principles, risk controls, model oversight, data stewardship, and policy guardrails.

1. Solution Shaping and Delivery Oversight

Shape the solution mix across data strategy, data governance, information architecture, analytics, generative AI, large language models, retrieval-augmented generation, agentic workflows, automation, and cloud data platforms.
Provide financial oversight for programs, including forecasting, budgeting, commercial tracking, margin management, and value realization.

1. Go-to-Market Leadership

Partner with account teams, industry leaders, alliance partners, and technology practices to identify opportunities, shape pursuits, and develop compelling client proposals.
Lead or contribute to executive-level sales conversations, diagnostics, pitches, proposals, statements of work, and orals.

1. Offering Development and Practice Building

Lead the development and continuous refinement of Data and AI Strategy and Advisory offerings, including methods, playbooks, maturity models, assessment tools, business case templates, roadmap frameworks, governance models, and reusable accelerators.
Develop differentiated propositions across areas such as AI strategy, generative AI readiness, agentic AI adoption, data governance, data product strategy, AI operating models, AI value realization, and responsible AI.

1. Thought Leadership and Market Presence

Create and contribute to executive thought leadership on Data and AI strategy, responsible AI, generative AI, agentic AI, data governance, AI operating models, and AI-enabled transformation.
Represent the practice through client briefings, webinars, roundtables, conference participation, white papers, blogs, points of view, and internal leadership forums.

1. People Leadership and Talent Development

Lead, mentor, and develop consultants, strategists, architects, analysts, and delivery professionals within the Data and AI Strategy and Advisory sub-practice.
Foster a culture of curiosity, commercial accountability, inclusion, collaboration, innovation, and continuous improvement.

Required Experience and Qualifications
Strong understanding of data strategy, data governance, information architecture, data platforms, analytics, and AI-enabled business transformation.
Working knowledge of generative AI, large language models, retrieval-augmented generation, agentic AI, automation, responsible AI, and AI governance.
Familiarity with cloud data and AI ecosystems such as Microsoft Azure, Databricks, Snowflake, AWS, Google Cloud, OpenAI, or similar platforms.
Experience with analytics and data visualization tools such as Power BI, Tableau, Alteryx, or equivalent platforms.
Familiarity with AI cost modeling, including cloud consumption, licensing, model usage, fine-tuning, operations, support, and value realization economics.

The base compensation range for this role in the posted location is $179,624 to $269,436.
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may