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.