HZ Hossein Zandinejad Supply Chain Analytics & ML

Skills & tools

The pieces I reach for most, grouped by what they're for rather than how impressive they sound.

Languages & tools

Python SQL VBA Advanced Excel Git GitHub Jupyter VS Code

Data & ML

Pandas NumPy Scikit-learn Exploratory Data Analysis Statistical Analysis Logistic Regression Random Forest XGBoost Clustering Anomaly Detection Feature Engineering KPI Design Data Quality

AI & NLP

Large Language Models Prompt Engineering Generative AI NLP AI-assisted Process Automation

Automation & BI

Python & Excel Automation xlwings REST APIs Streamlit Power BI Plotly Matplotlib

How these come together

Model it

Statistical grounding from a BASc in Statistics plus hands-on ML — logistic regression, random forest, and XGBoost — used to replace guesswork with scored decisions, like the stocktaking model that lifted ROC-AUC by 20%.

Automate it

Python and Excel automation, REST APIs, and Streamlit turn a repeatable manual task into a tool a team can run themselves — the difference between a 2-hour report and a 10-minute one.

Report it

KPI design and Power BI / Plotly dashboards make the result visible to the people who need it — weekly and monthly reporting that ten departments actually read.