Small, reproducible Python demos (synthetic data) illustrating how scientific and data workflows support decisions. Each example links to source under demos/ in this repository.
Demand and uncertainty
Forecast monthly demand with prediction intervals to frame inventory risk.
A/B testing decisions
Turn experiment results into effect sizes, confidence intervals, and a plain-language decision.
Segmentation
Cluster customers or products and summarize each segment with interpretable profiles.
Margin what-if
Explore price and cost sensitivity with simple elasticity-style scenarios.
Ticket themes over time
Track synthetic support themes weekly to spot emerging issues.
Repeatable weekly report
Generate a templated HTML report from CSVs with Python and Jinja2.