Data science
Cross-disciplinary field: statistics + programming + domain expertise to extract insights from data. "Sexiest job of the 21st century" (HBR 2012). 2020+ role shift toward ML engineer.
Classic tools: Python (pandas, scikit-learn, statsmodels), R (tidyverse), Jupyter Notebooks, Tableau/PowerBI for viz. Pipeline: collection → cleaning → exploratory data analysis (EDA) → modeling → interpretation. CRISP-DM is the classic process framework. The 2020s differentiate: data analyst (SQL + viz), data scientist (statistics + ML), ML engineer (deployment + MLOps), AI engineer (LLM applications, RAG). Major platforms: Databricks, Snowflake, Posit Workbench.