Position Overview
As the organization accelerates its AI adoption, the AI Strategy & Governance Specialist will play a central role in ensuring responsible, standardized, and effective AI implementation enterprise-wide.
Reporting to senior technology and business teams, this position blends deep technical proficiency with high-level strategic insight to set foundational governance structures for AI initiatives across the organization.
Responsibilities
Lead the creation and standardization of AI operational manuals, playbooks, and guidelines for application across varied organizational use cases.
Collaborate with business teams to extract diverse AI implementation learnings and consolidate them into cohesive organizational frameworks for AI deployment.
Establish and maintain policies aligning AI initiatives with evolving national and industry standards, while adhering to the latest regulatory expectations.
Partner with risk, legal, and compliance departments to develop protocols that ensure responsible AI practices—including robust data security, ethics, and risk frameworks.
Cultivate and sustain relationships with internal business and technical stakeholders to ascertain AI requirements and synchronize solutions with business priorities.
Regularly update executive leadership and technical leaders on the progress and direction of AI strategy implementation, surfacing critical challenges and opportunities.
Work closely with the DSA AI Partnership Lead to coordinate projects in tandem with partners such as A*STAR and GovTech, supporting a rapid and innovative AI adoption process.
Benchmark and adapt international AI best practices, ensuring that organizational AI strategies remain agile, ethical, and at the forefront of industry advancement.
Requirements
Bachelor's, Master's, or PhD degree in Analytics, Artificial Intelligence, Data Science, Computer Science, Computer Engineering, or Information Systems (specializing in business analytics or data science) from a recognized academic institution
OR
Relevant professional certifications in business analytics, data science, or machine learning engineering from accredited professional bodies, accompanied by substantial related professional experience for candidates from other disciplines.
At least 1 year working within AI governance frameworks, and a minimum of 1 year implementing AI or machine learning projects.
Proven ability to manage multiple projects simultaneously within a dynamic, matrixed, and agile work environment.
Strong critical thinking, attention to detail, and the capacity to communicate complex technical concepts effectively to a variety of internal and external stakeholders.
Comprehensive knowledge of AI technologies, frameworks, and their practical application in real-world organizational contexts.
Familiarity with emerging AI regulatory trends, industry standards, and responsible AI principles.
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