Artificial Intelligence Specialist

Role Summary

Senior Data Consulting Lead with deep expertise in Data Architecture, Data Products, and AI-led Platforms, specialising in Insurance (with focus on Specialty Lines). This role drives enterprise-scale data and AI transformation, shaping modern data ecosystems, AI platforms, and AI-driven migration strategies on Azure, Databricks, and Power BI. A recognised thought leader, responsible for influencing C-level stakeholders, defining strategy, and delivering measurable outcomes through data + AI convergence.

Key Responsibilities

1. Data Strategy, AI Vision & Thought Leadership

• Define enterprise-wide data and AI strategy aligned to business and regulatory priorities
• Act as a trusted advisor to CIO/CDO/AI leadership, shaping data & AI transformation roadmaps
• Drive data product thinking with embedded AI/ML capabilities (intelligent underwriting, claims automation, pricing optimisation)
• Bring market perspective on AI-native data ecosystems, GenAI enablement, and agentic architectures

2. Data & AI Architecture Leadership

• Own end-to-end architecture across data and AI layers:
• Data ingestion, processing, modelling, semantic layer, and consumption
• AI platform integration (model lifecycle, feature engineering, inference pipelines)
• Design modern Lakehouse + AI architecture leveraging Azure and Databricks
• Define architecture for scalable, governed, and reusable AI-ready data platforms
• Ensure integration of data governance, lineage, security, and responsible AI principles

3. AI Platforms & AI-led Data Migration

• Design and implement AI Platforms integrating:
• Model development environments, MLOps pipelines, feature stores, and model serving
• Lead AI-driven migration strategies, including:
• Automated schema discovery, data mapping, and transformation using AI accelerators
• AI-assisted code conversion (e.g., legacy ETL → modern pipelines)
• Intelligent data quality assessment and anomaly detection
• Drive adoption of AI-enabled accelerators to:
• Reduce migration timelines
• Improve accuracy and minimise manual intervention
• Enable continuous intelligence through pipelines that combine data engineering with AI/ML workflows

4. Insurance Domain & Data Products

• Deep understanding of Specialty Lines insurance (Commercial, Marine, Liability, etc.)
• Define and operationalise domain-centric data products, such as:
• Risk profiling and underwriting intelligence
• Claims analytics and fraud detection models
• Pricing optimisation models
• Customer and broker analytics platforms
• Align data products to business outcomes, regulatory compliance, and monetisation opportunities

5. Technology Leadership (Azure + Databricks + Power BI)

• Lead architecture and execution of:
• Azure Data Platform (ADF, Synapse, Fabric, ADLS)
• Databricks (Lakehouse, Delta, ML workflows, PySpark pipelines)
• Power BI (semantic models, enterprise dashboards, self-service BI)
• Drive adoption of:
• Metadata-driven architectures
• Automation, orchestration, and reusable frameworks
• Ensure separation and optimisation of data engineering, analytics, and AI workloads

6. Consulting & Delivery Leadership

• Lead end-to-end consulting engagements (Discovery → Architecture → Delivery → Value Realisation)
• Run executive workshops on Data Strategy, AI adoption, and operating models
• Define target operating models (Data + AI CoE, Data Product organisation)
• Mentor teams across architecture, engineering, analytics, and AI
• Build reusable accelerators and GTM offerings in data + AI transformation

Required Experience & Skills

Core Experience

• 12–18+ years across Data, Analytics, AI Platforms, and Architecture
• Proven leadership of large-scale data and AI transformation programmes
• Strong experience in consulting, stakeholder engagement, and solution shaping

Insurance Expertis

• eStrong domain expertise in Insurance (with exposure to Specialty Lines
• )Understanding of underwriting, claims, pricing, regulatory reporting data model
• sExperience mapping data products to insurance business capabilitie

s
AI & Data Platform Experti

• seExperience designing and implementin
• g:AI/ML platforms (MLOps, model lifecycle management, feature store
• s)AI-enabled data pipelines and intelligent automation framewor
• ksExposure t
• o:GenAI / LLM use cases in data (RAG, knowledge graphs, copilot
• s)AI-driven migration an d code/data modernisation approach

es
Technical Expert

• iseStrong hands-on / architectural expertise
• in:Azure data ecosystem (ADF, Synapse, Fabric, AD
• LS)Databricks (Delta Lake, Spark, ML workflo
• ws)Power BI (enterprise analytics & semantic lay
• er)Strong grounding
• in:Data modelling (dimensional, domain-driv
• en)Data governance, lineage, catalogu
• ingIntegration patterns (batch, streaming, AP

Is)Leadership & Consulting Ski

• llsExecutive stakeholder engagement (CIO/CDO/AI leade
• rs)Ability to transla te business problems into data + AI soluti
• onsStrong storytelling and influencing capabil
• ityExperience buildi ng data/AI CoEs and scalable delivery mod