The Data & Artificial Intelligence Strategy professional will lead technology transformation Data Management and AI initiatives with hands-on experience and a solid track record in project delivery. The candidate combines strong technical expertise with strategic insight and practical implementation skills ideally from technology consulting digital implementation or operational technology backgrounds.
Key Accountabilities
- AI Implementation: Lead the end-to-end deployment of AI solutions that create measurable business value. This involves collaborating with data scientists engineers and business stakeholders to design develop and scale AI models and applications that address key organizational challenges. Ensure AI initiatives are aligned with business priorities and monitor their impact through key performance indicators.
- Technology Project Execution: Take ownership of technology projects from initiation to completion ensuring they are delivered on schedule within budget and meet quality standards. This includes detailed project planning resource allocation risk management and continuous communication with stakeholders. Apply best practices in project management to navigate challenges and remove blockers for successful delivery.
- Data & Analytics: Oversee data management and analytics activities to ensure data quality governance and accessibility. Guide the development of data pipelines analytics models and reporting frameworks to empower data-driven decision-making across the organization. Stay current with industry trends in data technologies and AI to recommend enhancements and innovations.
- Digital Engineering: Provide technical guidance on software development life cycles architecture design and integration practices. Work closely with engineering teams to ensure that digital solutions are robust scalable and maintainable. Encourage adoption of agile methodologies and continuous improvement in engineering processes.
- Technology Assessment: Conduct regular reviews of technology capabilities identifying gaps and opportunities for improvement. Evaluate emerging technologies for relevance and potential business impact. Develop recommendations and roadmaps for technology upgrades that support strategic goals.
- Automation Implementation: Drive initiatives that leverage technology and AI to automate repetitive tasks and optimize operational workflows. Collaborate across departments to identify automation opportunities and lead pilot projects to test and refine automation solutions ensuring efficiency gains and cost reductions.
- Technical Guidance: Act as a bridge between technical teams and business units by translating complex technical concepts into clear actionable insights. Facilitate understanding and alignment among diverse stakeholders to support effective decision-making and foster innovation.
- Contributing to Strategy: Support senior leadership by assessing current technology and AI strategies identifying risks and opportunities and developing actionable plans for execution. Work closely with strategy teams to ensure that technology roadmaps align with the overall business vision and market dynamics.
- Vendor Assessment: Evaluate technology vendors tools and service providers to ensure they meet organizational needs in quality cost and capability. Lead vendor selection processes including due diligence pilot evaluations and contract negotiations and manage ongoing vendor relationships.
- Project Oversight: Manage external consultants and technology vendors engaged in projects to ensure delivery meets specifications and timelines. Provide clear direction monitor progress and coordinate efforts between internal teams and external partners to maintain project momentum.
Requirements
10 to 15 years of relevant experience
Bachelors degree in Computer Science Data Science Artificial Intelligence or related field; Masters degree preferred
Practical expertise in machine learning models data processing and AI implementation methods
Proven experience scaling technology solutions and understanding system architecture
Strong analytical and problem-solving capabilities
Ability to align technology initiatives with business objectives
Excellent communication skills adaptable to various audiences
Effective stakeholder relationship management
Commitment to quality attention to detail and results orientation
The Data & Artificial Intelligence Strategy professional will lead technology transformation Data Management and AI initiatives with hands-on experience and a solid track record in project delivery. The candidate combines strong technical expertise with strategic insight and practical implementation...
The Data & Artificial Intelligence Strategy professional will lead technology transformation Data Management and AI initiatives with hands-on experience and a solid track record in project delivery. The candidate combines strong technical expertise with strategic insight and practical implementation skills ideally from technology consulting digital implementation or operational technology backgrounds.
Key Accountabilities
- AI Implementation: Lead the end-to-end deployment of AI solutions that create measurable business value. This involves collaborating with data scientists engineers and business stakeholders to design develop and scale AI models and applications that address key organizational challenges. Ensure AI initiatives are aligned with business priorities and monitor their impact through key performance indicators.
- Technology Project Execution: Take ownership of technology projects from initiation to completion ensuring they are delivered on schedule within budget and meet quality standards. This includes detailed project planning resource allocation risk management and continuous communication with stakeholders. Apply best practices in project management to navigate challenges and remove blockers for successful delivery.
- Data & Analytics: Oversee data management and analytics activities to ensure data quality governance and accessibility. Guide the development of data pipelines analytics models and reporting frameworks to empower data-driven decision-making across the organization. Stay current with industry trends in data technologies and AI to recommend enhancements and innovations.
- Digital Engineering: Provide technical guidance on software development life cycles architecture design and integration practices. Work closely with engineering teams to ensure that digital solutions are robust scalable and maintainable. Encourage adoption of agile methodologies and continuous improvement in engineering processes.
- Technology Assessment: Conduct regular reviews of technology capabilities identifying gaps and opportunities for improvement. Evaluate emerging technologies for relevance and potential business impact. Develop recommendations and roadmaps for technology upgrades that support strategic goals.
- Automation Implementation: Drive initiatives that leverage technology and AI to automate repetitive tasks and optimize operational workflows. Collaborate across departments to identify automation opportunities and lead pilot projects to test and refine automation solutions ensuring efficiency gains and cost reductions.
- Technical Guidance: Act as a bridge between technical teams and business units by translating complex technical concepts into clear actionable insights. Facilitate understanding and alignment among diverse stakeholders to support effective decision-making and foster innovation.
- Contributing to Strategy: Support senior leadership by assessing current technology and AI strategies identifying risks and opportunities and developing actionable plans for execution. Work closely with strategy teams to ensure that technology roadmaps align with the overall business vision and market dynamics.
- Vendor Assessment: Evaluate technology vendors tools and service providers to ensure they meet organizational needs in quality cost and capability. Lead vendor selection processes including due diligence pilot evaluations and contract negotiations and manage ongoing vendor relationships.
- Project Oversight: Manage external consultants and technology vendors engaged in projects to ensure delivery meets specifications and timelines. Provide clear direction monitor progress and coordinate efforts between internal teams and external partners to maintain project momentum.
Requirements
10 to 15 years of relevant experience
Bachelors degree in Computer Science Data Science Artificial Intelligence or related field; Masters degree preferred
Practical expertise in machine learning models data processing and AI implementation methods
Proven experience scaling technology solutions and understanding system architecture
Strong analytical and problem-solving capabilities
Ability to align technology initiatives with business objectives
Excellent communication skills adaptable to various audiences
Effective stakeholder relationship management
Commitment to quality attention to detail and results orientation
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