A hands-on virtual internship exploring retail transaction data through customer segmentation, uplift testing, and strategic commercial insights — the way Quantium's data teams actually work.
This repository contains all deliverables from the Quantium Data Analytics Virtual Job Simulation hosted on Forage. The simulation mirrors real-world analytics workflows at Quantium — one of Australia's leading data science and analytics firms — spanning data wrangling, statistical experimentation, and executive storytelling.
📦 Forage_Quantium_Data_Analytics
┣ 📁 Task 1: Data Preparation and Customer Analytics
┃ ┣ 📓 Jupyter Notebook (.ipynb)
┃ ┗ 📊 Power BI Report (.pdf)
┣ 📁 Task 2: Experimenting and Uplift Testing
┃ ┗ 📓 Jupyter Notebook (.ipynb)
┣ 📁 Task 3: Analytics and Commercial Application
┃ ┗ 📊 Presentation (.pptx)
┗ 🏅 Completion Certificate (.pdf)
"Understand the who behind the what."
Dived deep into Quantium's retail transaction dataset to uncover who is buying chips and why. Performed rigorous data cleaning, feature engineering, and customer segmentation to identify high-value customer groups and their purchasing behaviours.
Key Highlights:
- 🔍 Cleaned and standardized raw transaction & customer data
- 👥 Segmented customers by lifestage and premium tier
- 📈 Identified top-performing customer segments by sales contribution
- 📊 Visualized insights in Power BI for stakeholder reporting
| Deliverable | Link |
|---|---|
| 📓 Python Jupyter Notebook | Open in nbviewer → |
| 📊 Power BI Analysis PDF | View Report → |
"Did the trial stores actually make a difference?"
Applied control store methodology to evaluate the performance of trial store layouts. Used statistical techniques to identify the best-matched control stores and measure incremental sales uplift with confidence.
Key Highlights:
- 🏪 Matched trial stores to statistically similar control stores
- 📉 Conducted pre/post performance comparisons
- 📐 Applied Pearson correlation & magnitude distance scoring
- ✅ Validated uplift significance using hypothesis testing
| Deliverable | Link |
|---|---|
| 📓 Python Jupyter Notebook | Open in nbviewer → |
"Translate numbers into a story the boardroom actually cares about."
Synthesized insights from Tasks 1 & 2 into a polished executive presentation tailored for the Category Manager. Communicated findings in a clear, data-backed narrative with actionable commercial recommendations.
Key Highlights:
- 🗣️ Built a compelling story around the data insights
- 💼 Aligned recommendations with business objectives
- 🎨 Designed a professional slide deck using the Quantium template
- 📌 Prioritised actionable next steps for the client
| Deliverable | Link |
|---|---|
| 📊 PowerPoint Presentation | View Slides → |
| Tool | Purpose |
|---|---|
| Python (pandas, matplotlib, scipy) | Data wrangling, EDA, statistical testing |
| Jupyter Notebook | Interactive analysis & documentation |
| Power BI | Customer analytics dashboard |
| Microsoft PowerPoint | Executive presentation |
| Excel | Supplementary data handling |
Successfully completed all three tasks and earned the official Quantium Data Analytics Job Simulation Certificate from Forage.
Built with 📊 data, ☕ coffee, and a passion for turning raw numbers into real decisions.
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