About

I'm Reggie Alderson, a Data Scientist and Analytics Engineer based in Sydney, with six years' experience building the data systems that sit behind customer-facing analytics products — and, increasingly, applied AI.

Most recently at Pearson, I owned the analytics layer of a job market analytics API used by business and government customers across Australia, Canada, the UK, and the US — pipelines built on Databricks and AWS, processing hundreds of millions of job ad records. I introduced richer features, including semantic descriptions and hard negative examples, into the anomaly detection pipeline, improving skills-mapping accuracy by 4% and cutting false positives by roughly 20%. I also led a vendor consolidation that reduced two external data providers down to one.

Earlier, at NSW Health Pathology, I built automated ETL pipelines across four-plus laboratory systems and a Power BI dashboard giving near real-time instrument-health insights to around 60 laboratories statewide — replacing manual reporting that had previously required at least 20 staff.

I work primarily in Python and SQL, with production experience in Databricks, AWS, Azure Synapse, PySpark, and dbt. Outside work I've built a reproducible LLM pipeline that measures AI's effect on data-role skill demand, normalising ~11,300 skill phrases into a knowledge graph on BigQuery, and a dbt pipeline over a live Sydney Trains feed with data-quality testing and a DAMA-DMBOK governance layer — see Articles.

I'm open to Data Scientist, Analytics Engineer, and Data Engineer roles — get in touch.