Data Science
Statistical analysis, exploratory data analysis, feature engineering, and data storytelling.
Proficiency: Advanced
Workflow
- Data ingestion → Pandas + SQL / PostgreSQL
- EDA →
matplotlib,seaborn,plotly - Feature engineering → NumPy + domain knowledge
- Modelling → scikit-learn or PyTorch
- Reporting → Jupyter, Quarto, custom dashboards
Academic context
Directly supported by university coursework in Statistics, Mathematics, and Physics.
Related: Python, R, Statistics, Mathematics