Data Science Interviews is a community-curated collection of interview questions and answers for data science roles.
The project addresses the challenge of preparing for data science interviews by aggregating questions across multiple domains—theoretical concepts like linear models and neural networks, technical skills in SQL and Python, and probability—along with community-provided answers. The approach relies on collaborative contribution, where anyone can submit new questions, improve existing answers, or correct mistakes through pull requests.
Candidates preparing for data science positions should use this resource to study across the breadth of topics commonly covered in interviews. The collection suits those seeking a structured, crowdsourced alternative to scattered online resources. The project explicitly organizes material by category, making it easier to focus on specific weak areas rather than searching through unstructured question banks.
The project maintains an open contribution model where improvements flow continuously from the community. The repository includes a dedicated contributors file acknowledging those who have shaped the collection, and the maintainer actively promotes the resource through social channels and a related community platform for data discussions.
