AI Specialist, Group Data & Analytics, Group Strategy & Innovation

Maybank; Kuala Lumpur; On-site; MYR 368,000 - 531,000; Full time

Job summary

Maybank is seeking an AI Lead to assess and qualify AI opportunities, validate business needs, design solutions, ensure data readiness, and plan integrations before investments are made.

You will drive the design, development, and iteration of AI solutions, provide governance, define evaluation frameworks, build reusable assets, and contribute to enterprise strategy while coaching teams for safe, scalable AI adoption.

Qualifications

• Hands-on data science or AI solution delivery experience.
• Strong Python and SQL skills with modern ML/LLM tooling.
• Experience in regulated industries or banking is a plus.
• Ability to translate ambiguous business needs into scoped solutions.

Responsibilities

• Assess and qualify AI opportunities, validating needs, feasibility, design, data sources, integrations and delivery approach.
• Lead the design, development and iteration of AI solutions and proofs of concept, ensuring simple viable approaches and production transition.
• Provide technical advisory and governance for AI initiatives across business units and guardrails.
• Define, implement and monitor AI evaluation frameworks with metrics and drift/bias monitoring.
• Develop reusable AI assets, pipelines, and reference architectures to accelerate delivery.
• Contribute to enterprise AI strategy, roadmaps and governance decisions with evidence-based recommendations.
• Act as AI SME and deliver training, awareness, and coaching to enable safe, scalable adoption.

Skills

Python

SQL

ML frameworks

LLM/Prompt design

Agent design

Retrieval-augmented generation

Cloud platforms

MLOps / LLMOps

Data-driven communication

Problem translation

Education

Degree in Computer Science, Data Science, Statistics, Engineering, Mathematics

Job description

• Assess and qualify AI opportunities, validating business needs, technical feasibility, solution design, data sources, integrations, and delivery approach before development investment is committed.
• Lead the design, development, and iteration of AI solutions and proofs of concept, ensuring the simplest viable approach is adopted and supporting transition to production.
• Provide technical advisory and governance for AI initiatives across business units, reviewing solution designs, model selection, architectures, and adherence to enterprise standards and guardrails.
• Define, implement, and monitor AI evaluation frameworks, including performance metrics, benchmarking, validation criteria, and ongoing assessment for drift, degradation, bias, and overall effectiveness.
• Develop and maintain reusable AI assets and enterprise standards, including pipelines, evaluation frameworks, reference architectures, prompt patterns, and technical guidance to accelerate delivery and reduce duplication.
• Contribute to enterprise AI strategy and roadmaps, recommending appropriate delivery models, reusable components, effort estimates, and supporting governance decision-making through evidence-based recommendations.
• Act as an AI subject matter expert and enabler, delivering training, awareness initiatives, technical guidance, and coaching to support safe, scalable, and responsible AI adoption across the organisation.

Requirement:

• Degree in Computer Science, Data Science, Statistics, Engineering, Mathematics or a related quantitative discipline.
• Solid hands-on experience delivering data science, machine learning or generative AI solutions
• Strong practical command of Python and SQL, modern ML and LLM frameworks, prompt and agent design, retrieval-augmented generation, and cloud-based AI platforms.
• Ability to translate ambiguous business demand into a scoped, testable solution, and to communicate clearly with both senior stakeholders and non-specialist users.
• Experience in banking, financial services or another regulated industry, and familiarity with model risk, data privacy and AI governance expectations.
• Exposure to MLOps and LLMOps practice: versioning, deployment, monitoring, drift detection and cost management of live AI services.