Maybank Group is the leading financial services provider in Malaysia catering to the needs of consumers, investors, entrepreneurs, non-profit organizations, and corporations. The group, which has expanded internationally, has the largest network among Malaysian banks of over 2,400 branches and offices in 20 countries, employing over 44,000 Maybankers and serving over 22 million customers. It is the only regional bank with a presence in all 10 ASEAN countries (as of November 2016).

By strengthening our core business and franchise, we gain a competitive advantage by achieving synergies across our diverse group. Domestically we aim to achieve leadership across key and profitable segments. Internationally we capture value from new investments and continue to pursue organic expansion by delivering innovation and superior customer value. We constantly seek to enhance performance management and achieve cost optimization by focusing on effective IT operations and enhancing employee productivity.

Job Description :

Responsibilities :

- Act as the bridge between business stakeholders, data scientists, and engineering teams to ensure alignment on goals and deliverables.

- Work effectively with multiple stakeholders in a global, cross-functional environment.

- Collaborate with business teams to define product functionality, features, and roadmap.

- Prioritise effectively and navigate ambiguity to drive outcomes that maximise business value.

- Strong understanding of ML algorithms, deep learning frameworks, and their application to real-world problems.

- Collaborate with data scientists to support model development, validation, deployment, and monitoring.

- Solid foundation in statistics, hypothesis testing, and probability for interpreting data and validating models.

- Define, prioritise, and manage the product backlog for data science and machine learning initiatives, Gen-AI use cases and statistical models.

- Maintain and refine backlog items to ensure the team focuses on features with the highest business impact.

- Drive the end-to-end product lifecycle, from ideation to delivery and continuous improvement.

- Oversee data governance, quality, and compliance aspects relevant to AI/ML solutions.

- Partner with monitoring teams to track post-deployment model performance and ensure ongoing optimisation.

Requirements :

- Graduate/PG degree/Certification in Data Science or AI.

- Professional qualifications, such as an MBA, will be an added advantage.

- 12-16 years of relevant banking/ finance industry experience combined with software product development.

- Excellent knowledge of AGILE software development methodology and basic SQL.

- Excellent knowledge of Product Implementation.

- Interpersonal and leadership skills.

- Teamwork.

- Intellectual curiosity.

- Financial business acumen.

- Effective communication.

- Knowledge of data visualization, functional design (from data capture to application design and MIS creation), and experimentation frameworks (MVPs, pilots, hypothesis testing).

- Knowledge of banking processes such as lending and deposits.

- Exposure to micro services architecture and modern software product lifecycle practices.

- Exposure to risk analytics and risk management practices.

- Strong conceptual foundation in banking operations and regulatory compliance.

- Proficiency in Python (preferred) or R and SQL, with experience in large-scale data handling, building data/process pipelines, and leveraging cloud platforms.