I am an analytics specialist and industrial engineer with six years of experience supporting decision-making in operations across Energy, Education, and Consumer Packaged Goods (CPG) industries. I am skilled in analytics engineering, applied statistics, data visualisation, and continuous improvement. I believe that analytics should be reliable. Reliability emerges from smooth operation, which is a consequence of deliberate design.

In my current role at Pearson, I lead efforts around data stewardship and governance, and build pipelines to support international teams.

In previous roles, I have focused on improving analytics infrastructure and processes. I have delivered a change-detection system that processes 15,000 SKUs/minute for forecast reviews; streamlined queries to reduce the runtime by 90%; implemented data quality monitoring that pre-empted ~2,000 support tickets; and automated reporting processes to simplify KPI tracking. I have also ported forecasting models to enable hydropower operations planning and spearheaded kaizen initiatives across business processes.

Tools and technologies I use:

• Methods: ANOVA, Linear mixed models, Marginal effects, Time series analysis, Six Sigma
• Programming: SQL, R, Python, D3.js
• Data platforms: PostgreSQL, BigQuery, Databricks, Alteryx, Tableau