Graeme Watson

Background

About Graeme Watson

I build and ship data products end to end. I scope the problem, design data models and pipelines, train and evaluate models, and deliver decision-ready outputs. I also handle the roadmap, success metrics, and stakeholder alignment so the work generates value. Anomaly detection: architected and deployed a rules-based meter anomaly system that doubled the validated detection rate (Databricks/PySpark/SQL, surfaced in Power BI). Forecasting: building a self-tuning forecasting tool with Monte Carlo scenarios for budget and project planning. Platform & quality: parameterized notebooks, CI/CD, and data checks; migrated to matured tables; performance tuning across PySpark/SQL/Delta Lake on Azure. People & delivery: guide contracted data engineers and a contracted developer, mentor a co-op, run reviews, and present to leadership to drive adoption. AI in practice: daily use of Claude and OpenAI/ChatGPT via the OpenAI SDK, plus Google tools, for design drafts, code review, test generation, documentation, and automation that reduces manual reporting and pipeline toil. Stack: Databricks, PySpark, SQL, Delta Lake, Azure, Power BI, time-series forecasting, anomaly detection, Monte Carlo, MLOps, product roadmapping, stakeholder management.