Data & AI Strategist

Job responsibilities

• Data & AI Pipeline Ownership: Own the origination, qualification, development and progression of Data & AI opportunities. Build and maintain a pipeline capable of delivering $30M+ in bookings, anchored on $3–5M+ deal sizes, shifting composition toward strategic, transformation-led programs rather than fragmented work.Build pipeline across the full spectrum — data platforms, governance, and AI — working with clients and account teams to translate emerging needs into defined transformation opportunities. Shape opportunities as integrated data-to-AI value chains rather than siloed initiatives, defining the client problem, intended business outcomes, transformation pathway and relevant Data & AI capabilities.
• Pursuit & Deal Shaping: Lead the shaping of complex Data & AI pursuits, owning the client narrative, business case, transformation agenda, and value proposition, solution direction and commercial framing. Drive opportunity progression and materially influence conversion, deal size, and win rates.Lead solutioning that connects data foundations with AI capabilities into one coherent transformation narrative, strengthening technical credibility and deal differentiation.
• Executive Client Advisory & Opportunity Development: Build trusted executive relationships in partnership with account leadership with senior client stakeholders including CDOs, CIOs, CTOs, and Heads of AI. Lead executive conversations on how Data & AI investments translate into business outcomes such as growth, efficiency, and risk reduction.Advise executives on how data readiness underpins successful AI adoption, helping sequence investment across the data-to-AI maturity curve.Use Data & AI expertise to explore client challenges, identify potential value and help define where a viable transformation opportunity exists.
• EMEI Data & AI Growth Strategy: Support the Data & AI growth agenda in EMEI. Identify priority accounts, whitespace, and repeatable plays that scale Data & AI revenue, grounded in real client problems and market demand.Identify whitespace across the integrated stack — data platforms and AI capabilities — with go-to-market plays that show a clear path from one to the next.Translate recurring client needs and market insight into repeatable transformation propositions, plays and opportunity patterns that strengthen the Data & AI pipeline across markets and accounts.Partner with Client Partners to focus Data & AI effort where it can create the greatest client and growth opportunity.
• Solution & Offering Leadership: Work with Practice Leaders, Ecosystem teams, architects, and SMEs to shape solutions that are differentiated, relevant, and grounded in delivery capability. Connect data platforms, governance, AI/ML, and agentic enterprise data foundations to tangible business outcomes. Requires hands-on experience with Agentic AI solutions and use case execution.Maintain a reusable library spanning data architecture and AI solution patterns to speed up assembly of end-to-end offerings.Partner with architects on feasibility across the stack — data integration, model selection, and tooling — to ensure proposed solutions are deliverable.