How AI Decision-Making is Improving Enterprise Outcomes
Blog
Highlights
5+ Years
Immediate or max 30 days’ Notice Period
Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or related field.
Job Description
At Beinex, we are looking for a strategic and forward-thinking Data Strategy Consultant. The ideal candidate will play a key role in shaping enterprise-wide data strategies, defining future-ready operating models, and guiding clients through large-scale digital and AI transformation initiatives. This role requires a strong blend of business consulting, data management expertise, stakeholder engagement, and strategic problem-solving capabilities to deliver impactful, value-driven outcomes across industries.
Responsibilities
- Develop end-to-end data and AI strategies for client organizations, aligned with their business objectives, industry context, and transformation priorities.
- Define target-state data operating models, including data governance structures, data architecture, capability requirements, and ways of working.
- Build multi-year data and AI roadmaps that sequence initiatives based on business value, dependencies, and organizational readiness.
- Identify and shape high-impact data and AI use cases, developing business cases that quantify value, investment, and expected outcomes.
- Advise client leadership on strategic choices around data platforms, architecture direction, sourcing models, and build-vs-buy decisions.
- Conduct focused diagnostics of the client's current data landscape where needed to inform strategic recommendations.
- Engage with C-level and senior stakeholders to socialize recommendations, build consensus, and drive strategic decisions.
- Research industry trends, emerging technologies, regulatory shifts, and competitor benchmarks to inform forward-looking strategy.
- Translate complex data and AI concepts into clear, executive-ready narratives and compelling strategic recommendations.
- Collaborate with internal data engineering, analytics, and AI teams to pressure-test strategies for technical feasibility and implementability.
- Create high-impact client deliverables, including strategy decks, operating model designs, roadmap documents, and board-level recommendations.
- Act as a support point for business development by contributing to RFP responses, client proposals, and solution demonstrations.
- Build and maintain strategy frameworks, methodologies, and reusable assets to strengthen the firm's data strategy practice.
Key Skills & Requirements
- Develop end-to-end data and AI strategies for client organizations, aligned with their business objectives, industry context, and transformation priorities
- Define target-state data operating models, including data governance structures, data architecture, capability requirements, and ways of working.
- Build multi-year data and AI roadmaps that sequence initiatives based on business value, dependencies, and organizational readiness
- Identify and shape high-impact data and AI use cases, developing business cases that quantify value, investment, and expected outcomes
- Advise client leadership on strategic choices around data platforms, architecture direction, sourcing models, and build-vs-buy decisions
- Conduct focused diagnostics of the client's current data landscape where needed to inform strategic recommendations
- Engage with C-level and senior stakeholders to socialize recommendations, build consensus, and drive strategic decisions
- Research industry trends, emerging technologies, regulatory shifts, and competitor benchmarks to inform forward-looking strategy
- Translate complex data and AI concepts into clear, executive-ready narratives and compelling strategic recommendations
- Collaborate with internal data engineering, analytics, and AI teams to pressure-test strategies for technical feasibility and implementability
- Create high-impact client deliverables, including strategy decks, operating model designs, roadmap documents, and board-level recommendations
- Act as a support point for business development by contributing to RFP responses, client proposals, and solution demonstrations
- Build and maintain strategy frameworks, methodologies, and reusable assets to strengthen the firm's data strategy practice
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