Enterprise AI and Analytics Leader

Tennant Company•Eden Prairie, MN

1d•Onsite

About The Position

The Senior Manager, Enterprise AI and Analytics Leader is responsible for defining and executing the enterprise strategy for artificial intelligence, data, analytics and governance. This leader will transform data into a strategic enterprise asset, enabling business growth, operational excellence, innovation, and competitive advantage. The role serves as the leader of the Enterprise AI Center of Excellence (CoE) and is accountable for establishing enterprise-wide capabilities, governance, platforms, standards, and adoption strategies that enable responsible, scalable, and value-driven use of AI, Analytics and data. Working closely with business leaders, technology teams, and executive leadership, this position drives the organization's data and AI agenda by aligning investments to business priorities, accelerating digital transformation, and delivering measurable business outcomes.

Requirements

15+ years of experience in IT, software engineering, data platforms, or enterprise architecture.
5+ years leading enterprise AI, Machine Learning, or Data Science initiatives.
Experience dealing with Analytics platforms like SAP and Non SAP solutions
Experience delivering large-scale cloud and AI transformation programs.
Proven success influencing executive stakeholders and driving cross-functional initiatives.
Generative AI, LLMs, Agentic AI, Retrieval-Augmented Generation (RAG)
AI frameworks such as Semantic Kernel, LangChain, CrewAI, AutoGen
Azure AI Foundry, Azure OpenAI, Azure Machine Learning
Cloud platforms (Azure preferred; AWS/GCP a plus)
MLOps, LLMOps, CI/CD, DevSecOps
Data platforms including Databricks, Fabric and modern data architectures
API, microservices, containerization, and Kubernetes
Experience in SAP Joule
Experience with Analytic platforms like SAP Business Data Cloud, BW, Databricks, Fabric

Nice To Haves

Experience in Manufacturing Industries.
Experience implementing Responsible AI frameworks.
Demonstrated thought leadership in AI strategy and enterprise transformation.
Demonstrated experience in leading and dealing with analytics strategy and execution

Responsibilities

Define and Execute the enterprise AI & analytics, data strategy aligned with corporate objectives.
Develop a multi-year roadmap that advances business intelligence, predictive analytics, machine learning, generative AI, and data-driven decision making.
Identify opportunities to leverage data and AI to improve customer experience, operational efficiency, revenue growth, and innovation.
Advise executive leadership on emerging trends, risks, and opportunities related to data and artificial intelligence.
Establish success metrics and value realization frameworks for all major initiatives.
Lead the Enterprise AI Center of Excellence.
Develop and execute the enterprise AI roadmap and use-case portfolio.
Establish AI governance, operating models, and responsible AI principles.
Identify and prioritize high-value AI opportunities across all business functions.
Oversee deployment and scaling of generative AI, machine learning, intelligent automation, and advanced analytics solutions.
Establish standards for AI development, model management, prompt engineering, and AI lifecycle management.
Ensure AI initiatives deliver measurable business value and align with strategic priorities.
Establish enterprise data governance policies, standards, and accountability models.
Lead master data management, data quality, metadata management, and data stewardship programs.
Ensure data is managed as a strategic enterprise asset.
Develop enterprise data architecture and information management standards.
Partner with business leaders to improve data ownership, accountability, and trust.
Lead enterprise reporting, analytics, and business intelligence capabilities.
Drive adoption of self-service analytics and data-driven decision making.
Establish standards for reporting, dashboards, KPIs, and performance management.
Ensure business leaders have timely access to trusted and actionable information.
Advance predictive and prescriptive analytics capabilities across the enterprise.
Establish enterprise AI governance frameworks and oversight processes.
Ensure compliance with legal, regulatory, privacy, cybersecurity, and ethical requirements.
Chair the AI Governance Council and provide executive-level reporting on AI risks and performance.
Develop policies for responsible AI usage, model monitoring, explainability, and risk management.
Partner with Legal, HR, Risk, Compliance, and Security teams to ensure effective governance.
Act as a strategic advisor to business leaders on data and AI opportunities.
Facilitate business prioritization of data and AI investments.
Build strong partnerships across Manufacturing, Supply Chain, Commercial, Service, Finance, HR, and Corporate Functions.
Lead value realization reviews and ensure business outcomes are achieved.
Promote a culture of data literacy and AI-enabled innovation.
Define standards supporting data, analytics, and AI.
Partner with Enterprise Architecture and Infrastructure teams to establish scalable and secure platforms.
Drive cloud-based data and AI platform modernization.
Ensure integration of AI capabilities into core business applications and business processes.
Manage vendor relationships and strategic technology partnerships.
Build and lead a high-performing team of data, analytics, and AI professionals.
Develop enterprise data literacy and AI literacy programs.
Foster a culture of innovation, collaboration, accountability, and continuous improvement.