Information Technology - Senior Data Scientist (Advanced AI Track)

Join SIA's in-house AI Center of Excellence, which runs the company's shared AI platforms and delivers LLM and AI agent products to business units. Key Responsibilities • Build and operate shared AI platforms: a multi-provider LLM gateway, an agent orchestration layer, an evaluation and monitoring layer, and a staff assistant. • Deliver LLM and agent applications for business units, from prototype to live service with measurable business results. • Evaluate AI systems: build test sets; measure groundedness, factual accuracy, task-success rate, safety, latency, reliability and model or data drift; define release gates and rollback criteria; manage model upgrades and retirements. • For agentic workflows, evaluate tool-call accuracy, policy compliance, unauthorized-action prevention and human-escalation effectiveness. • Balance cost and performance: route between models, use batch processing, and run models on our own GPUs when data cannot leave the company. • Design how agents retrieve and share business knowledge, with access control and data governance across SIA and Group companies. • Apply traditional machine learning and optimization to fraud and anomaly detection, forecasting, resource optimization and document classification. Decide when a classic model beats an LLM. • Work with Data Engineering, Enterprise Architecture and other teams as the technical go-to person in your area. • Work with business units to define the problem and success measures, explain results in plain language, and confirm the business outcome after launch. • Plan and run AI projects end to end: scope, milestones, cross-team coordination, and clear status and risk reporting to management. Requirements: • Business communication: you find the real problem behind a request, explain limits without jargon, and renegotiate scope when needed. • Curiosity: you try new models and tools on real problems, and investigate the cause of unexpected behavior. • Logical thinking: you break vague problems into parts, state assumptions, and support conclusions with evidence. • Can-do attitude: you take ownership, find a way forward when the first approach fails, and raise risks early. • Project management: milestones, realistic estimates, stakeholder updates, and plan changes across more than one team. • Mentoring skills to guide junior data scientists. • Degree in computer science, machine learning or a related field, or equivalent experience. • Strong Python and SQL; 3+ years delivering ML or AI systems to production. • Traditional ML: gradient-boosted trees, regression, forecasting, clustering, anomaly detection, feature engineering, validation, and knowing when a simple model is better. • LLM applications with commercial or open-weight models (Claude, GPT, Gemini, AWS Bedrock): prompts, retrieval, tool calling and multi-step agents. • Structured evaluation and monitoring of LLM systems in production (test sets, automated checks, quality, safety, latency, reliability, drift), including tool-call accuracy and policy compliance for agents. • Responsible AI: measurable controls such as guardrails, groundedness checks and audit trails, plus data privacy and access control (for example PDPA). • Secure cloud deployment (AWS, Azure or GCP) and cost management. • Experience taking an AI or analytics solution beyond launch and measuring its impact on revenue, cost, productivity, service quality or operations. Preferred • Advanced degree in a related field • TypeScript, Java or Scala • Model Context Protocol (MCP) • GPU model serving, PyTorch, self-hosted open-weight models • Optimization, causal methods, advanced experiment design • Aviation or travel experience Only shortlisted candidates will be notified.