Professional Overview
Applied AI engineer bridging enterprise data and GenAI. 3+ years across BigQuery, Snowflake, Fabric, Vertex AI, Databricks, and Claude API. Shipped AI for Fortune 50 retail ($5M revenue protected) and Fortune 100 telecom (94% query cost cut via Vertex AI agent). Three live open-source products: agentic spreadsheet, DB cost CLI, and voice AI app.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built Vertex AI (Gemini) BigQuery cost intelligence agent end-to-end.
- 94% reduction in bytes scanned; $4,500/table/year projected savings.
- Automated Oregon trouble report VBA: 45-min manual to 30-sec auto run.
- Migrated Oracle PL/SQL to BigQuery for Quantum Fiber divestiture.
- Built SOPs and audit trails for PUC filings across 8 US states.
Key Achievements / KPIs
- 94% reduction in BigQuery bytes scanned per query
- $4,500/year projected savings per production table
- 45-min manual report cut to 30 seconds (3,800 cells)
- Zero-error Oracle to BigQuery migration under deadline
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Led Walgreens supply chain AI POV; protected $5M revenue, 200+ stores
- Anomaly detection cut unplanned supply disruptions by 28%
- +34% forecast accuracy with Scikit-learn predictive models
- Architected Grab IoT pipeline: ADF + Synapse + Power BI
- ABARTA BI on Snowflake + Fabric: $42K/yr saved, 7 BUs
Key Achievements / KPIs
- $5M revenue protected via Walgreens supply chain AI
- +34% forecast accuracy gain
- 28% drop in unplanned supply disruptions
- $42K/yr enterprise BI savings for ABARTA
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built Power BI dashboards surfacing 12 high-risk safety issues
- SharePoint + Power Automate workflows cut manual reporting 30%
- Surfaced hidden operational risk via process intelligence
Key Achievements / KPIs
- 12 high-risk safety issues uncovered for leadership
- 30% reduction in manual reporting time
Education
Field of Study: Business Management, Ad Personalisation, Data Privacy, Consumer Behaviour
Field of Study: Information Technology, NLP, Machine Learning
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
