- Bachelor’s degree in computer science, Data Science, Engineering, or a related field, or comparable hands-on experience.
- 10+ years of experience in senior technology, manufacturing, and/or business leadership roles, with a proven track record of leading AI/ML initiatives. Demonstrated success delivering AI solutions from concept through full-scale enterprise deployment, ideally within complex, operational environments.
- Deep expertise in artificial intelligence and machine learning, including areas such as machine learning, deep learning, predictive analytics, and decision intelligence. Hands-on experience with modern AI/ML tools, frameworks, and platforms, with the ability to integrate AI solutions into existing systems and workflows.
- Proven ability to define and execute an AI strategy aligned to business objectives. Experience leading enterprise-wide digital or AI transformation initiatives and managing cross-functional teams (e.g., data science, engineering, operations) to deliver scalable, production-ready AI solutions.
- Strong business acumen with the ability to align AI initiatives to measurable business outcomes and KPIs (e.g., yield, efficiency, quality, cost). Experienced in developing business cases for AI investments and tracking their operational and financial impact.
- Exceptional communication and stakeholder management skills, with the ability to translate complex AI concepts into clear, actionable insights for executive and non-technical audiences.
- Demonstrated ability to influence senior leaders and drive cross-functional alignment to support AI adoption at scale.
Desirable Skills, Competencies & Experience:
- Advanced Education: Master’s or Ph.D. in a relevant field (e.g., Computer Science, Artificial Intelligence, Data Science), or an MBA with strong technology or digital focus.
- Industry Domain Experience: Experience in manufacturing, supply chain, or industrial operations. Familiarity with Industry 4.0 concepts and technologies, including Manufacturing Execution Systems (MES), IoT/OT environments, and digital twin platforms.
- AI Governance & Responsible Innovation: Knowledge of AI ethics, governance, and regulatory compliance, with experience establishing responsible AI practices across the enterprise.
- Thought Leadership & Continuous Learning: Recognized contributions to the AI community (e.g., speaking engagements, publications, or industry group participation).
- Relevant professional certifications (e.g., AI/ML, cloud platforms) or evidence of ongoing learning in emerging AI technologies are an advantage.