Career Profile
Results-driven analyst with five years of experience across building materials, property, and retail. Proficient in Google Analytics, SQL, Python, and Power BI, with actual projects data record of building analytics functions from the ground up using real project data. Experienced in developing pipeline dashboards, managing CRM data, delivering KPI reporting, and automating workflows. Combines hands-on industry knowledge in construction supply with strong data knowledge to generate insights that reflect real operational conditions, including procurement cycles, pricing trends, and seasonal performance.
Skills
Data & Analytics: SQL, Power BI, Python, Excel, KPI Dashboards, Data Visualisation
CRM & Sales Platforms: BCI Central, EstimateOne, Monday.com, MYOB, Xero
Sales Operations: Pipeline Management, B2B Sales, Market Research, Procurement Tracking
Professional: Detail Oriented, Self-starter, Adaptable, Cross-team Collaboration
Employment History
Showtile
December 2023 - Present
Sales Operations Analyst
Tiles, Stone & Pavers, Sydney, NSW
- Redesigned and automated CRM data entry processes. Cut duplicate records and made pipeline reports reliable.
- Tracked 15+ international procurement pipelines across supplier quotes and delivery schedules, cutting order mismatches by 30%.
- Managed sales data and invoice reconciliation across MYOB and Xero for 200+ accounts.
- Prepared PowerPoint performance reports on sales trends and stock levels for management review.
HTT Flooring
July 2022 - December 2023
Account Manager
B2B Flooring Wholesale, Sydney, NSW
- Conducted territory analysis across 4 markets, found 35% of revenue concentrated in one region, rebalanced focus and grew portfolio by 15%.
- Administered CRM data across 3 platforms for 300+ B2B accounts, maintaining 98% data accuracy.
- Built reporting workflows across sales, warehouse, and logistics, eliminating 3 manual handoffs and cutting response time by 40%.
Royal Crystal Group
May 2020 - July 2022
Sales Representative & Business Development
International B2B, Flooring, Remote from Vietnam in Sydney
- Produced competitor analysis across 20+ flooring brands. The pricing review that followed lifted margins by 12%.
- Managed cross-border operations across 2 time zones with a 95% on-time delivery rate.
- Led the Sydney Build trade event, managing a $15K budget and generating 50+ qualified leads.
Spire Property Group
December 2020 - March 2023
Key Account Manager
Property, Sydney, NSW (Concurrent)
- Built weekly pipeline dashboards for 8 key accounts ($2M+). Caught three at-risk accounts early and kept $350K from walking out.
- Delivered quarterly performance presentations to the C-suite. Analysis influenced $500K+ in quarterly resource allocation decisions made by leadership.
- Kept CRM records at 99% accuracy across 100+ accounts.
Projects
SQL - Retail Business Analysis
T-SQL, CTEs, Window Functions, Dynamic PIVOT
T-SQL, CTEs, Window Functions, Dynamic PIVOT
- Question: At which discount tier does each product category shift from profit to loss?
- Key results: Discounts above 50% produce losses across all categories. Technology is the top profit driver for Consumer and Corporate segments even though it is not always the top revenue category.
SQL - AU Building Approvals
T-SQL, LAG(), Conditional Aggregation, Seasonal PIVOT
T-SQL, LAG(), Conditional Aggregation, Seasonal PIVOT
- Question: Which states are gaining construction market share, and which are declining?
- Key results: Victoria leads with 31% of national approvals vs NSW at 28%. NSW has fallen 41% from its 2016 peak. Only Tasmania and South Australia grew across both periods.
Python - Customer Sentiment Analysis
Python, VADER, TextBlob, NLP, pandas, matplotlib
Python, VADER, TextBlob, NLP, pandas, matplotlib
- Question: Does what customers write in a review match the star rating they give?
- Key results: VADER sentiment correlates 0.681 with star ratings. Quality and durability is the #1 complaint (41% of negative reviews). 3.9% of reviews show text-star mismatches.
Python - Housing Feature Impact
Python, pandas, matplotlib, statistical comparison
Python, pandas, matplotlib, statistical comparison
- Question: Which building materials and finishes have the biggest dollar impact on sale price?
- Key results: Stone masonry veneer adds $102K vs no veneer. Kitchen upgrade from Average to Excellent adds $80K+. Poured concrete foundation is $43K above cinder block.
Power BI - Pizza Retail Dashboard
Power BI, DAX, Excel
Power BI, DAX, Excel
- Question: When do customers order, what do they order, and which products drive the most revenue?
- Key results: Friday is the highest revenue day. Classic category leads in both order count and revenue. Peak hours are 12-1pm and 5-7pm.
Education
Master of Marketing
· Western Sydney University
Jan 2022 - Jan 2024
Bachelor of Commerce, International Business
· Macquarie University
Feb 2016 - Nov 2019
Diploma of Commerce
· SIBT Navitas, Sydney
Feb 2014 - Dec 2015
Certifications
- Google Analytics Individual Qualification
- Data Visualization: Storytelling (LinkedIn Learning)