Hi, I’m Ahmad Arif — an Applied Data Analyst / Data Scientist with a background in Computer Science and a Master’s degree in Business Analytics.
This portfolio showcases end-to-end analytics and data science projects focused on transforming raw data into actionable insights, predictive models, and business decisions using Python, SQL, and Power BI.
My work reflects real-world data roles — from problem definition and data preparation to analysis, modelling, visualisation, and stakeholder-focused recommendations.
Product & Growth Analytics | Python, SQL (SQLite), Power BI
An end-to-end analysis of user behaviour across an e-commerce funnel (View → Cart → Purchase).
Key highlights:
- Built a sequential, user-level funnel to avoid misleading event-based metrics
- Validated Python analysis using SQL CTEs and window functions
- Designed an interactive Power BI dashboard with KPIs and daily conversion trends
- Translated insights into business-focused recommendations to improve conversion performance
📁 Folder: data-analytics/ecommerce-funnel-analysis/
Business Performance Analytics | Python, SQL, Power BI
- Analysed transactional retail data to calculate revenue, order volume, AOV, and product performance
- Built interactive Power BI dashboards to support commercial decision-making
- Focused on KPI tracking, trend analysis, and performance drivers
📁 Folder: data-analytics/retail-ecommerce-performance/
Customer Analytics | Python, SQL, Pandas, Power BI
- Conducted customer-level cohort and retention analysis
- Measured repeat behaviour and churn patterns over time
- Identified high-value customer segments and engagement trends to support retention strategy
📁 Folder: data-analytics/customer-retention-analysis/
This section will include applied data science and predictive modelling projects, such as:
- Customer churn prediction
- Demand forecasting
- Pricing or revenue optimisation
Each project will demonstrate:
- Feature engineering and model development
- Model evaluation and interpretation
- Business-focused insights and recommendations
📁 Folder: data-science/
- Languages: Python, SQL
- Analytics & Modelling: pandas, NumPy, funnel analysis, cohort analysis, forecasting
- Visualisation: Power BI, Tableau
- Data Handling: Data cleaning, feature engineering, large datasets
- Other: Git, GitHub, Excel
- Processed data outputs are generated by notebooks and not committed to keep the repository lightweight
- Sample data and clear documentation are provided where applicable
- Each project includes problem statements, analysis notebooks, SQL scripts, and business insights
I am targeting Data Analyst, Applied Data Scientist, Product / Growth Analyst, and Junior Data Scientist roles in the UK, where I can contribute to data-driven and predictive decision-making.
- LinkedIn: https://www.linkedin.com/in/ahmadaarif
- GitHub: https://github.com/ahmadaarif