AI Systems Analyst

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related field.
• Minimum 6+ years of relevant experience in AI systems analysis, data architecture, analytics, or similar roles.
• Strong experience in data architecture design across Data Lake and Data Warehouse environments.
• Hands-on experience designing NLP and AI use cases (Text classification and categorization, Named entity extraction, Risk indicator identification, Summarization of documents, alerts, or cases).
• Strong experience in requirements analysis, solution design, and translating business needs into technical specifications.
• Proven ability in effort estimation, project scoping, and delivery planning for technical initiatives.
• Experience reviewing and validating test strategies, functional test cases, and data validation frameworks.
• Strong understanding of enterprise data platforms and data lifecycle management.
• Ability to design logical data layering and curation strategies supporting AI, analytics, and reporting use cases.
• Experience working in regulated environments such as banking, financial services, or other compliance-heavy industries is highly preferred.
• Strong understanding of risk management, governance, and compliance requirements in data and AI systems.
• Experience working with unstructured data and enterprise-scale data processing systems.
• Familiarity with AI/NLP-based analytics implementations in production or enterprise environments.
• Roles and Responsibilities:
• Analyze business, regulatory, and compliance requirements and translate them into scalable technical and AI-enabled solution designs.
• Design and define data architectures supporting AI and NLP use cases across data lakes and data warehouse platforms, including ingestion, curation, and governance of structured and unstructured data.
• Translate business requirements into NLP-driven analytical use cases such as text classification, entity extraction, risk indicator identification, and summarization of alerts, cases, and documents.
• Define logical data layering and curation strategies to support reporting, analytics, and AI/ML workloads.
• Perform detailed effort estimation for projects, enhancements, and change requests, ensuring accurate delivery planning and resource alignment.
• Communicate complex technical, architectural, and AI concepts to business stakeholders and senior leadership in a simplified and structured manner.
• Review and approve test strategies, functional test cases, and data validation approaches to ensure alignment with business and technical requirements.
• Collaborate with data engineers, data scientists, and business analysts to ensure end-to-end solution feasibility and consistency.
• Support solution governance by ensuring compliance, data quality, and architectural standards across AI and analytics initiatives.
• Identify opportunities to enhance business processes using AI/NLP-driven insights and automation.
• Facilitate requirement gathering sessions and stakeholder workshops to align expectations and define solution scope.
• Please send your application highlighting:
• Your relevant experience
• Current/expected salary
• Availability information
• A latest MS-WORD Resume
• **We regret that only short-listed applicants will be contacted.**
• Note: GECO Asia is an Information Technology Consulting Services provider. We provide specialist IT and Digital Transformation specialist resources on a project (SOW) and/or permanent basis. We operate under a Comprehensive License offered by Ministry of Manpower, Singapore.
• [GECO

Additional Information

Job Summary Role: AI Systems Analyst Start: ASAP Duration: 12 Months Location: Singapore We are seeking an experienced AI System Analyst with 6+ years of relevant experience in data architecture, AI/NLP use case design, and enterprise analytics systems. The ideal candidate will play a key role in bridging business, regulatory, and technical teams by translating complex requirements into scalable AI-enabled solutions, with a strong focus on NLP-driven analytics and enterprise data platforms. This role requires deep understanding of data lake and data warehouse architectures, unstructured data processing, and AI/NLP use case implementation. The successful candidate will support solution design, effort estimation, test strategy validation, and stakeholder communication across business and technical domains, particularly in regulated environments such as banking and financial services.

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