Thi Chung

Data Science graduate with strong analytical and commercial acumen, experienced in analysing large datasets, identifying trends and translating insights into business decisions. Skilled in Databricks, SQL, Python, Advanced Excel, Power BI and Tableau with hands-on experience in data analysis, reporting automation, data quality and cross-functional business analysis.

Junior HR Analyst at Optiver (2026-02 – 2026-07)

• Analysed global workforce datasets using SQL, Python and Databricks to identify trends, investigate patterns and provide insights supporting business and HR decision-making.
• Built and maintained analytical dashboards including Gender Pay Gap, Spans and Layers reporting using Python, SQL, Databricks Apps and Power BI.
• Migrated recurring reporting workflows to Databricks such as Leave of Absence, Risk Compliance Committee, Talent Review improving data accessibility, consistency and efficiency across reporting processes.
• Performed ad hoc analysis, investigating data issues and working with cross-functional stakeholders to improve data quality and reporting accuracy.

HR Analyst at KPay Group (2025-11 – 2026-02)

• Analysed 6,000+ candidate records weekly to identify trends and characteristics associated with successful Business Development candidates, supporting data-driven talent decisions.
• Built a BI dashboard comparing successful and unsuccessful candidates, translating recruitment data into actionable insights for the Talent Acquisition team.
• Developed a GPT-powered CV extraction model to automate candidate data processing, reducing processing time from several minutes to approximately 6 seconds per CV.

Business Analyst at Argiro Credit Platform (2025-01 – 2025-04)

• Audited financial data and OCR outputs against source documents, identifying and documenting 50+ discrepancies to improve data accuracy and reliability.
• Developed a text-classification model matching 1,000+ internal financial codes with Bloomberg codes, achieving 90% accuracy and reducing manual mapping workload.
• Translated business requirements into platform features and user stories, working with technical and business stakeholders to deliver data-driven solutions.
• Created AI-assisted swimlane analyses comparing automated and traditional workflows, helping communicate efficiency improvements and commercial benefits to clients.

Data Scientist at Australian Botanic Garden (2024-07 – 2025-07)

• Analysed 16,000+ species records using Python and build dashboard using Plotly library to identify patterns and drivers of plant rarity across large datasets.
• Applied statistical and machine learning models to 200+ plant species to quantify relationships between environmental and biological variables.
• Developed and evaluated multiple machine learning models to predict missing flowering times, achieving 80% accuracy with a K-Nearest Neighbour model.

Bachelor in Data Science – SP Jain School of Global Management (2022-09 – 2025-05)