Business Transformation Senior Advisor

Dataiku
United States, RemotePosted 7 April 2026

Job Description

Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack — empowering organizations to run AI across multi-vendor environments with centralized governance. The world’s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog , LinkedIn , X , and YouTube . About the Role Dataiku is seeking a Senior Business Transformation Advisor to join our well-established Business Transformation Americas Practice. The Business Transformation team operates as an internal consulting organization with a threefold mission: Support customer-facing teams in delivering transformative value for our customers Guide customers through the full AI maturity journey—from traditional analytics through generative AI to agentic AI deployment—focusing on sustainable value creation, governance, and enterprise-scale adoption Accelerate Dataiku's transformation from software vendor to strategic partner Dataiku is on a rapid growth path, having recently surpassed $350M in ARR with global operations across the Americas, Europe, and Asia. The ideal candidate would be based in the US and reports to the Business Transformation Americas regional lead. Job Responsibilities Value Engineering AI Strategy Create and implement value realization frameworks connecting AI initiatives to measurable business outcomes, including ROI modeling for generative and agentic AI implementations Design AI operating models enabling organizations to scale from experimentation to production, including governance frameworks, center of excellence structures, and responsible AI practices Navigate the AI maturity curve with clients, developing roadmaps from traditional analytics through advanced agentic workflows Content Development Standardization Build programmatic content for customer-facing teams on value realization and AI transformation Develop and standardize in-house toolkits and methodologies to drive consistency and excellence Key Performance Areas Strategic Deal Acceleration Value Positioning Proactively engage with account teams across AMER sub-regions to articulate Dataiku's unique value proposition in enabling end-to-end AI lifecycle management—from data preparation through traditional ML, generative AI, and agentic workflows Position unified platform advantages through executive case for change artefact, addressing CIO, CDO concerns around AI ROI, governance, security, and scalability Enablement, Coaching Collaboration Mentor Account Executives in value-driven selling, providing targeted guidance to navigate complex sales landscapes and improve deal progression and win rates Support regional GTM teams on estate modernization programs External Brand Thought Leadership Represent Dataiku through speaking engagements at conferences, partner, and industry events Contribute thought leadership on agentic AI ROI, adoption patterns, AI maturity models, production AI challenges, responsible AI frameworks, and value realization in AI systems Build credibility as an expert on enterprise AI transformation, not just tool implementation Required Qualifications: 5-10 years of experience in AI strategy or management consulting developing and delivering value frameworks Track record of delivering and capturing value for RPA, Analytics, or AI client engagements to very large organizations Deep understanding of AI technology landscape (traditional ML, generative AI, agentic AI architectures) Proven ability to translate technical AI capabilities into business value propositions for C-suite audiences Experience advising on A ... (truncated, view full listing at source)
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