Director - Data Science

Role Overview:

- Owning enterprise AI strategy across Generative AI, Agentic AI, and ML platforms - from long-term vision through production deployment and measurable value realisation.

- Deep hands-on expertise in multi-agent orchestration, LLM/SLM infrastructure, RAG pipelines, Knowledge Graphs, NLP, multimodal AI, MLOps, and responsible AI governance.

- Proven track record establishing reference architectures and reusable AI frameworks at org scale, with multi-million-dollar cost savings and measurable operational impact delivered at Apple, Morgan Stanley, and beyond.

- Recognised technical force multiplier and C-suite advisor - builds high performing AI engineering teams, drives AI readiness and data literacy org-wide, and represents the AI function at senior executive level.

Core Competencies:

- Multi-Agent AI Frameworks

- Business-Facing AI Applications

- LLM, SLM & GenAI Platforms

- RAG, Knowledge Graphs & Retrieval

- Computer Vision: OCR

- Forecasting Platform

- ML Platform & MLOps Architecture

- AI-Ready Data Foundation

Team Leadership:

- Scaled and managed a multi-tiered AI engineering organisation.

- Mentored senior engineers and AI scientists as a force multiplier.

- Set technical standards for AI development and AI readiness assessments org-wide.

- Owned platform KPIs - adoption, latency, cost per inference, and business value.