- Experience
- 5–8 yrs
- Salary
- —
- Openings
- 1
- Posted
- 4 weeks ago
- Work mode
- In office
- Education
- Advanced degree in AI, Data Science, Statistics, Computer Science, Engineering or related discipline
- Resume
- Required to apply
Where you'll work
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Job description
About the Role and Organization
As Singapore's pioneering bank since 1932, we have committed ourselves to supporting individuals and businesses to realize their ambitions through tailored services and innovative solutions. We are currently advancing our transformation journey by integrating technology and creativity to evolve into a future-ready learning organization. Our overarching goal remains unwavering—to become Asia's foremost financial partner promoting sustainable futures.
Join us to build the bank of tomorrow, redefine financial service delivery, thrive within collaborative and supportive teams, and contribute meaningfully to your community’s growth. Develop your career and learning extensively in a vibrant, technology-forward environment.
Role Purpose
Reporting to the Group Data Office’s Responsible AI Lead, the AI Validation Specialist plays a critical role in independently verifying the efficacy and compliance of essential AI models employed by the bank. This entails rigorous testing, risk identification, limitation detection, and offering strategic guidance to ensure AI is utilized safely and responsibly throughout the institution.
Key Responsibilities
- Independently validate machine learning models across their life cycle to ensure accuracy and compliance.
- Develop validation frameworks, methodologies, and test strategies tailored for Generative AI and agentic AI systems.
- Critically analyze evaluation outcomes focused on model performance indicators such as accuracy, factual correctness, retrieval quality, relevancy, and adherence to instructions.
- Assess reliability of human-labelled benchmarks against LLM-as-judge methods through calibration efforts.
- Systematically test AI guardrails and appraise agentic AI functionalities for appropriate tool usage, reversibility of actions, and incorporation of human oversight.
- Produce detailed and clear documentation encompassing validation results, uncovered risks, limitations, and actionable recommendations.
- Support internal communication and knowledge-sharing regarding validation findings and best practices.
- Enhance AI validation standards by contributing to methodology development, establishing evidence benchmarks, and creating reusable test assets.
- Offer expert guidance to cross-functional teams including Risk, Technology, Internal Audit, and business divisions concerning AI validation.
- Track advancements in AI technology, policy landscapes, and industry standards to continually refine validation protocols and compliance criteria.
Required Qualifications and Experience
- Advanced qualification in Artificial Intelligence, Data Science, Statistics, Computer Science, Engineering, or related AI Governance fields.
- Five to eight years of experience in model validation and testing within banking or regulated sectors, demonstrating application of traditional model risk controls to emerging AI areas such as Generative AI and agentic AI frameworks.
- Skill in critically evaluating complex AI ecosystems, recognizing potential risks, and suggesting robust control mechanisms.
- In-depth understanding of AI development lifecycle, bias mitigation, fairness, explainability, control implementations, guardrails, and ongoing monitoring concepts.
- Excellent communication capabilities for generating clear, decision-appropriate, and compliance-ready documentation; skilled at conveying technical and governance issues to senior executives and non-specialist audiences.
- Hands-on acumen in designing and executing validation strategies focused on Generative AI evaluations.
- Practical experience working with machine learning and Generative AI frameworks and cloud-based AI technologies.
Preferred Attributes
- Knowledge of MAS guidelines and other regulatory frameworks relating to AI risk, data governance, IT risk, information security, and vendor risk management.
- Experience with developing or managing platforms centered on model governance, risk oversight, and validation workflows.
- Participation in industry committees, regulatory workgroups, or forums dealing with AI policy and governance.
Benefits
Our compensation includes attractive base salaries along with a comprehensive benefits package tailored to diverse lifestyles. We foster community engagement and provide premier learning and professional advancement opportunities, ensuring your well-being, career progress, and aspirations are as prioritized as those of our clientele.
Minimum education
Bachelor's Degree