Topic

Data Science

Interview prep for Data Scientist roles at modern AI companies — grouped by the two archetypes hiring loops actually test for: product/analytics depth, and full-stack applied modeling.

Guides

2 guides

Product & Analytics Data Science

For founding-stage product DS and analytics-leadership roles. Built around HeyGen (founding Data Scientist) and Cohere (Lead Data Scientist, Analytics & Data Insights). 17 chapters on SQL, experimentation (A/B, MABs, causal inference), product metrics, predictive modeling for business, defining the data/experimentation stack, dashboards, and analytics leadership.

Interview Prep SQL & Experimentation Causal Inference Product Metrics Full-Stack & Applied Data Science

For senior/staff DS roles that ship production models end-to-end. Built around SentiLink (Staff Data Scientist, Full Stack — fraud & identity) and Archetype AI (Data Scientist — multimodal sensor/prompt workflows). 17 chapters on ML fundamentals, feature engineering, imbalanced data, prompt engineering, time-series & signals, data pipelines, production ML, MLOps, and AWS data stack.

Interview Prep Production ML Fraud & Identity Time-series & Signals