Role Overview
This is a newly created position within the Chief Data Office of a Financial services client. It is both hands-on and strategic, requiring a deep technical background in data science and AI, combined with the ability to translate that knowledge into governance, risk controls, and enterprise frameworks.
Unlike traditional paper-based governance approaches, this role is about modernizing and automating governance processes, using advanced analytics, AI, and ML techniques. You will design control artefacts, test and evaluate models, and build frameworks that ensure responsible, secure, and effective use of AI across the organization.
This is a global role with high visibility, contributing directly to enterprise-wide transformation initiatives in AI and data risk management.
Key Responsibilities
- AI/ML Risk & Governance
Assess risks associated with data, cloud, and AI/ML models, including emerging areas such as Generative AI.
Design and implement automated controls to replace manual governance processes.
Develop frameworks to evaluate and monitor models, ensuring responsible and ethical AI. - Technical Data Science Leadership
Build and optimize ML models for anomaly detection, decision trees, and smart data quality checks.
Create enterprise platforms for testing, validating, and continuously monitoring AI/ML use cases (including LLMs).
Translate advanced algorithms into actionable governance solutions that manage AI risk. - Solution Delivery & Collaboration
Work with cross-functional teams (data engineers, developers, business SMEs) to deliver scalable AI governance solutions.
Act as a bridge between technical AI/ML development and governance/risk functions.
Provide leadership to a small team of data scientists and interns. - Continuous Learning & Transformation
Stay ahead of new AI regulations, cloud standards, and data governance requirements.
Introduce innovative approaches to embedding governance into AI/ML development.
Skills & Experience Required
- Master's degree in Data Science, Computer Science, or related field.
- 10+ years experience in data science/analytics, with strong knowledge of machine learning, statistical modeling, and algorithm design.
- Proven ability to build and manage end-to-end model pipelines (training, testing, deployment, monitoring).
- Strong Python skills, including use of relevant ML/AI libraries.
- Experience with cloud platforms (AWS, GCP, Azure) and hybrid/on-prem environments.
- Deep understanding of how algorithms work, beyond just API integration.
- Exposure to data risk, governance, or regulatory aspects of AI/ML is highly desirable.
- Excellent communication and stakeholder management skills able to explain technical concepts in business/risk terms.
- Experience leading small teams or mentoring junior data scientists.
Those who are keen for the role and would like to discuss the opportunity further, please click Apply Now or email Kin Long at [Confidential Information] with your updated CV.
Only shortlisted candidates will be responded to, therefore if you do not receive a response within 14 days, please accept this as notification that you have not been shortlisted.
Kin Long Fok
Morgan McKinley Pte Ltd
EA Licence No: 11C5502 | EAP Registration No: R2095054
