Deliver training programmes on Artificial Intelligence (AI) and data-driven solutions, contextualised for financial institutions.
Upskill finance professionals in practical AI use cases, including customer analytics and operational efficiency aligning with IBF Standards and regulatory expectations such as responsible AI, data governance, and model risk management.
Facilitate engaging and interactive learning sessions for diverse adult learners and incorporating financial sector case studies and real-world applications.
Job Requirement
Degree in Computer Science, Data Science, Statistics, Engineering, Finance, or related disciplines.
Relevant certification in the field of Learning & Development such as ACLP/ACTA is preferred.
IBF Standards certification or relevant professional qualification in AI Technology or related Financial Services disciplines with minimum 5 years of experience in the financial services sector is required.
Minimum of 3 years of experience delivering adult training (part-time or full-time), preferably for technical or technology-related programmes to finance professionals.
Demonstrated experience in applying AI, machine learning, data analytics projects in a financial institution or fintech environment (e.g. risk modelling, fraud analytics, customer analytics, credit scoring, robo-advisory, operations optimisation).
Demonstrates comprehensive understanding of:
Financial products and services (retail, corporate, wealth, payments, or other relevant segments).
AI lifecycle: data preparation, model development, validation, deployment and monitoring. Model risk management, data governance and responsible AI practices (e.g. fairness, explainability, transparency).
Proficient in MAS and industry guidance relevant to data, technology and AI (e.g. model governance, technology risk, conduct, data protection).
Strong analytical thinking skills, with the ability to translate complex AI concepts into clear, accessible, and business-relevant learning content.
Prior experience in delivering IBF STS or accredited programmes is preferred.
