Principal Data Scientist

Bank Islam Malaysia Berhad; Kuala Lumpur; On-site; MYR 300,000 - 400,000; Full time

Job summary

A major banking institution in Malaysia is seeking a Principal Data Scientist to lead and innovate high-value AI and ML initiatives. You will leverage your expertise to design scalable solutions across various banking sectors, mentor teams, and ensure compliance with ethical standards. This role requires a strong academic background, extensive experience in data analytics, and collaboration skills. Join us to shape our competitive advantage and drive impactful data initiatives.

Qualifications

• Strong academic qualifications, with an advanced degree in a quantitative discipline.
• Minimum 10–15 years experience in analytics infrastructure, business systems analysis.
• Broad experience with rapid prototyping on large datasets.

Responsibilities

• Lead scalable AI/ML model development with MLOps.
• Translate business challenges into structured data initiatives.
• Drive innovation with advanced AI and MLOps techniques.
• Mentor data scientists in ML methods and practices.

Skills

AI/ML model development

MLOps practices

Business intelligence

Collaboration with engineering teams

Education

Masters or PhD in a quantitative discipline

Job description

Principal Data Scientist

The Principal Data Scientist acts as a senior technical and strategic leader, driving high-value data science initiatives that shape the bank’s competitive advantage. This role combines deep expertise in AI/ML with strong business acumen to design, build, and deploy scalable, explainable, and impactful solutions across retail banking, corporate finance, trade services, and risk management.

Responsibilities

• Lead scalable AI/ML model development with MLOps for deployment, monitoring, and continuous improvement.
• Translate business challenges into structured data initiatives using reproducible, traceable MLOps practices.
• Drive innovation with advanced AI, ML, and MLOps techniques like CI/CD and containerization.
• Ensure MLOps-compliant models with governance, ethical standards, versioning, monitoring, and regulatory compliance.
• Mentor data scientists in ML methods and MLOps practices, improving operationalization and technical excellence.
• Collaborate with engineering teams to optimize pipelines, orchestration, and feature stores for production data.
• Monitor and optimize models through automated pipelines, drift detection, retraining, and continuous performance tracking.
• Partner across departments embedding AI/ML workflows, supported by MLOps for efficient integration.
• Communicate analytical results and provide MLOps dashboards, ensuring clarity and influencing strategic decisions.
• Automate AI/ML lifecycle stages—training, validation, deployment, monitoring—using MLOps to streamline and scale operations.

Requirements

• Strong academic qualifications, with an advanced degree (Masters or PhD) in a quantitative discipline (typically information technology, computer systems, or mathematics) and advanced software certifications will be an added advantage.
• Minimum 10–15 years with extensive experience in information technology analytics infrastructure, business systems analysis, business intelligence, application design, development, testing/software QA, implementation, coding, data modeling and reporting.
• Broad experience with rapid prototyping & production implementation on large datasets (terabytes/petabytes), aware of efficient algorithmic design, memory and CPU usage/scalability.
• In-depth experience developing advanced models impacting business & derived from business analytics utilizing the landscape of structured, unstructured data, transactional data, text and speech analytics.

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