# alexeygrigorev/data-science-interviews

Data science interview questions and answers

Repository: https://github.com/alexeygrigorev/data-science-interviews
Canonical: https://ross.abutalabs.com/products/data-science-interviews
Homepage: https://alexeygrigorev.com/data-science-interviews/
Language: HTML
License: CC-BY-4.0
License Family: other
Topics: data-science, machine-learning, interview-questions, data-science-interviews
Last push: 2026-08-18T07:04:22+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 35, longevity 100
- inputs: {"age_days": 2375, "days_push": 15, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 10131, forks 2157 (observed 2026-08-28T04:10:39.617458+00:00)

## What it is
A community-maintained collection of data science interview questions with answers, organized into theoretical (linear models, trees, neural networks) and technical (SQL, Python, coding) categories. It also includes contributed questions on probability and an awesome list of related interview resources.

## Use cases
- prepare for a data science interview
- practice machine learning interview questions
- review SQL and Python interview questions
- study theory questions about linear models and neural networks
- find data science interview resources
- contribute answers to data science interview questions

## When to choose
- you are preparing for data science or ML interviews and want community-vetted Q&A
- you want a free, openly licensed question bank covering theory, SQL, Python, and probability
- you want to contribute or improve interview answers via pull requests

## When to avoid
- you need structured courses or interactive practice platforms rather than markdown Q&A lists
- you need software engineering or system design interview prep outside data science
- you need guaranteed-accurate expert answers rather than community-contributed ones

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation
- domain: data-science, machine-learning, education, tutorials
- platform: -
- tags: interview-preparation, interview-questions, community-driven, sql, python, career, web-server

## Member repositories
- alexeygrigorev/data-science-interviews (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:39.617458+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:19:42.431385+00:00, confidence not recorded.
  - readme: https://github.com/alexeygrigorev/data-science-interviews (fetched 2026-08-28T04:10:39.617458+00:00, sha 107c59a8bb70)
  - homepage: https://alexeygrigorev.com/data-science-interviews/ (fetched 2026-08-29T08:19:20.457944+00:00, sha 42e73b0f203f)
- Data as of 2026-08-30T08:39:29.467469+00:00.