Melbourne, Victoria, Australia
Data Science graduate with a minor in Finance from the University of Melbourne, and additional studies in Applied Econometrics and Big Data from the London School of Economics. Experienced across finance, accounting, Enterprise Resource Planning (ERP), analytics, and machine learning in corporate, research, and client-facing environments. I am passionate about building a career in Data & Analytics, Finance, or Consulting, where I can use data, business understanding, and structured thinking to solve real problems. My value of "Excellence" drives me to keep growing through curiosity, humility, and challenging work, while contributing thoughtful solutions that create real value for the teams and communities I serve.
- Prepared SMSF financial statements, including balance sheets, profit and loss statements, and end-of-financial-year tax returns - Ensured compliance with ATO and regulatory requirements through accurate documentation, reconciliation, and review - Reviewed investment portfolios, financial reports, and supporting documents across asset classes including cash, term deposits, equities, ETFs, property, crypto, CFDs, options, warrants, forex, and IPOs
- Ranked as top performer in achieving hourly sales KPIs - Analysed customer traffic and conversion patterns through daily report
- Providing one-to-one lessons - Unpaid tutor for year 10-12 students
- Designed and implemented data pipelines - Collaborated with researchers to optimise algorithms large-scale quantum data analysis - Attended AMSI 2024 BioInfo Summer Symposium on quantum computing - Create Quantum Computing educational website
Project 1 – Oracle NetSuite Data Pipeline Implementation - Prepared, cleaned, and validated 10,000 employee records to ensure data accuracy - Deployed SQL-based data pipelines across HCM and ERP modules - Reduced integration errors by 80% - Executed go-live phase by monitoring system performance - Collaborated with cross-functional teams across HR, finance, and operations to align ERP data structures with business requirements and reporting needs Project 2 – Warehouse Capacity and Flow Analysis - Analysed 500+ SKUs and 6 months of warehouse movement data to identify approximately 25% warehouse overcapacity and bottlenecks - Built SQL and Python-based pipeline to analyse lead-time distributions and simulate inbound, dispatch, and re-slotting scenarios - Maximized storage limit in collaboration with logistics, inventory, and procurement teams - Reduced manual reporting time by approximately 5 hours per week by automating warehouse utilisation calculations and operational dashboard reporting - Designed actionable insights using Tableau for stakeholders