Data science interview prep, distilled into one very long bookmark

What it does This repository is a curated reading list for data science and machine learning interview preparation. The maintainer—a self-described frequent interviewer at large product companies and startups—has assembled external articles, videos, and guides covering resume writing, SQL, probability, statistics, and model-building fundamentals. Think of it as a single bookmark that tries to cover the entire screening-to-interview pipeline.

The interesting bit The curation is personal: the author claims to have verified and used most of the resources, and the advice ranges from tactical resume tips (keep it to two pages, quantify everything) to reminders that business understanding matters more after year three. It is unusually honest about the breadth of the field and admits the list is not exhaustive.

Key highlights

• Covers resume strategy, SQL, probability, statistics, linear algebra, and data preparation
• Includes non-technical advice: communication skills, networking, and portfolio building
• Curated from the author’s own interview experience at product-based companies and startups
• Explicitly warns that data science is a vast domain and the list is a starting point, not a bible
• Updated periodically with new resources

Verdict A useful starting point if you want a vetted pile of reading material before an interview loop. Not for you if you need interactive practice, original code, or a structured curriculum.