LinkedIn · Email · Sydney, NSW, Australia
I turn complex data into decisions that move businesses forward.
With 7+ years of analytical experience in the Australian pharmaceutical industry and a Master of Data Science from UNSW (WAM 79%), I bring a rare combination of deep domain expertise, technical capability, and commercial acumen — built across supply chain intelligence, business intelligence reporting, and enterprise data analytics.
I have spent my career embedded in high-stakes, regulated business environments where data quality, accuracy, and speed of insight directly impact operational and commercial outcomes. From designing SQL pipelines and building executive-facing Power BI and Tableau dashboards, to applying machine learning and statistical modelling across sales forecasting, demand planning, and supply risk — I deliver end-to-end analytical value.
Reduced financial claims by $1.5M within six months through structured data analysis and process optimisation. Recognised with the Bravissimo Award and contributed to the Best Team Award across three consecutive years.
| Category | Tools & Technologies |
|---|---|
| Languages | Python · SQL · R |
| BI & Visualisation | Power BI · Tableau · Excel · Power Query |
| Machine Learning | Scikit-learn · XGBoost · ARIMA · SARIMAX |
| Statistical Modelling | Regression · Classification · Time Series · Forecasting |
| Enterprise Systems | SAP · ERP Data Pipelines |
| Domain | Supply Chain Analytics · Demand Planning · Sales Forecasting · BI Reporting · Data Storytelling |
Forecasting daily electricity demand in NSW (2010–2021) using Random Forest, XGBoost, and ARIMA models. Includes feature engineering with lag variables, rolling statistics, and temperature data integration.
Python Machine Learning Time Series XGBoost ARIMA
End-to-end exploratory analysis of NASA GISS surface temperature data (1961–2019) across 284 countries. Covers OECD trends, seasonal decomposition, Mann-Kendall trend testing, and continental comparisons.
Python Statistical Analysis Climate Data Plotly Mann-Kendall
Predictive modelling for sustainable abalone harvesting using SVM classification and linear regression. Built a profitability estimation function combining shucked and viscera weight predictions.
R SVM Linear Regression Multivariate Analysis
- Master of Data Science — UNSW Sydney (WAM 79%)
- IBM Data Analyst Professional Certificate — Coursera
- Bachelor of Computer Science — Osmania University
Internship · Data Analyst / BI Analyst · MVP Studio, Sydney
Actively seeking Data Analyst, Data Scientist, or BI Analyst roles where I can contribute immediately, grow continuously, and deliver measurable impact.
Open to full-time opportunities across Sydney and remote roles in Australia.