Operational and revenue analysis for software solutions supporting services at Global Village UAE. Building Power BI dashboards and prototypes, examining profitability, and informing annual tender planning and revenue projections.
Evaluated high-volume AI-generated datasets, investigated recurring errors and quality patterns, and maintained structured evaluation benchmarks. Promoted from Research Associate in November 2025.
Python. SQL.
Power BI. Tableau.
Excel, and curiosity.
Pandas · NumPy · MySQL · Git · GitHub
AI & ML · Presidency University
2020–2024 · Bengaluru
QSpiders · 8-month bootcamp
Oct 2024–May 2025
Don’t just read the story. Explore it.
Preparing the public dataset.
A new interactive study using Chen, D. (2015), Online Retail · UCI, licensed under CC BY 4.0.
Complete months January–November 2011. Exact duplicates and cancellation invoices removed; positive quantities and prices only. Sales value is quantity × unit price and includes charges. Orders count distinct retained invoices. Returns are excluded, so values are not net revenue. This study uses its own scope and cleaning rules; totals differ from the resume project.
View the preparation code ↗From half a million transactions
to the details that make a difference.
Finding product, customer, and geographic patterns in e-commerce sales. A study in turning a large dataset into a useful business narrative.
How do products, customers, geography, and time shape sales performance?
Cleaned transactions, investigated missing values, removed duplicates, and validated records. Engineered revenue and time-based features, then explored product, customer, geographic, and monthly patterns.
Business-focused visualizations and insights from £10.25M+ in analyzed revenue, spanning 3,900+ products, 4,300+ customers, and 38 countries.
These figures describe the scope of the resume project, not revenue generated or business uplift.
Bringing factory and machine-level telemetry into focus through interactive visual analysis.
Where is downtime concentrated across factories and machine types?
Analyzed telemetry from four factories, created calculated fields, and built a Tableau dashboard with factory-level filtering.
Used Excel to classify employee compensation equality scores against defined fairness thresholds.
Completed as a job simulation; not employment at Deloitte.
Connecting ticketing activity with event performance and customer behavior through interactive Power BI reports.
What can event and ticketing data reveal about sales performance and customer behavior?
Analyzed event data and built dashboards with KPIs, filters, charts, and drill-down views.
Visual reports for monitoring performance and moving from headline metrics to detailed views of event and ticketing activity.
When I step away from the screen, I paint.
A few favourites from my canvas.
Have a data opportunity or an interesting question?
I’d love to hear what you’re working on.
