How datainterview.org checks its sources

Quotations
125
Organizations
18
Practice interviews
5
Sources checked
Nov 11, 2026

What is real

Every quotation is copied from the organization’s own publication and links to it. The site’s build compares each one, word for word, with a saved excerpt of that page, and fails if a word differs.

What is invented

The practice interviews are original. Waymark and every number, record and person in them are fictional. They are not any employer’s real interview questions.

Who publishes this

Socratify AI publishes and sponsors datainterview.org. Links to Socratify are marked as sponsored. Send a correction to hello@socratify.com.

Every source

Royal Statistical Society

American Statistical Association

Statistical Society of Australia

Flipkart

Monzo

  • We’re interested in how you structure the problem, what questions you ask, what assumptions you challenge, and how you move from ambiguity towards a recommendation.Monzo, Technology blog. Interviewing for Data Science at Monzo, Apr 27, 2026.
  • So we care about whether you can summarise results clearly and explain them in a way that works for a non-technical audience.Monzo, Technology blog. Interviewing for Data Science at Monzo, Apr 27, 2026.
  • spotting when visualisations or summaries might be misleading or incomplete.Monzo, Technology blog. Interviewing for Data Science at Monzo, Apr 27, 2026.
  • how you would approach a product or business problem, how you think about experimentation, what success metrics you would use, and how you’d reason about evidence, trade-offs, and next steps.Monzo, Technology blog. Interviewing for Data Science at Monzo, Apr 27, 2026.

Capital One

Spotify

  • Without offline-online signal calibration, our evals are opinions, not evidence.Matilda Ankargren and Mårten Schultzberg, Senior Data Scientist; Senior Manager/Staff Data Scientist. Better Experiments with LLM Evals — A funnel, not a fork, May 18, 2026.
  • the setting in which LLMs offer the most benefit for A/B testing is precisely where they are least likely to work. Human experiments therefore remain indispensable for true product innovation.Sebastian Ankargren, Joel Persson and Mårten Schultzberg, Senior Data Scientist; Research Scientist, Computational Economics; Senior Manager, Staff Data Scientist. When Can LLMs Replace Humans in A/B Tests?, Aug 13, 2026.
  • Not every change needs the same evidence: quick directional tests for iteration and data gathering, rigorous tests for ship decisions.Matilda Ankargren and Mårten Schultzberg, Senior Data Scientist; Senior Manager/Staff Data Scientist. Better Experiments with LLM Evals — A funnel, not a fork, May 18, 2026.
  • At Spotify, only about 12% of A/B tests end in a shipped positive result. Around 64% produce valid learningMatilda Ankargren and Mårten Schultzberg, Senior Data Scientist; Senior Manager/Staff Data Scientist. Better Experiments with LLM Evals — A funnel, not a fork, May 18, 2026.
  • Using those raw predictions in a standard experimental analysis recovered only 39% of the observed human treatment effect.Sebastian Ankargren, Joel Persson and Mårten Schultzberg, Senior Data Scientist; Research Scientist, Computational Economics; Senior Manager, Staff Data Scientist. When Can LLMs Replace Humans in A/B Tests?, Aug 13, 2026.
  • Evals verify: does the output conform to quality standards? Experiments validate: do real users respond as predicted?Matilda Ankargren and Mårten Schultzberg, Senior Data Scientist; Senior Manager/Staff Data Scientist. Better Experiments with LLM Evals — A funnel, not a fork, May 18, 2026.
  • LLM predictions can make human experiments better. They can be used to filter out weak ideas before they consume an experiment slot, or serve as covariates for variance reduction.Sebastian Ankargren, Joel Persson and Mårten Schultzberg, Senior Data Scientist; Research Scientist, Computational Economics; Senior Manager, Staff Data Scientist. When Can LLMs Replace Humans in A/B Tests?, Aug 13, 2026.

Grab

  • An agent can optimize only the world it is given; if that world has drifted from production, a faster loop will merely produce misleading answers sooner.Henokh Fibrianto and Larry Lin, Grab Tech Blog authors. Powering AI-led research through simulation, Oct 5, 2026.
  • The verdict is computed, not judged. The simulator computes its own metrics, which the agent can read but not redefine.Henokh Fibrianto and Larry Lin, Grab Tech Blog authors. Powering AI-led research through simulation, Oct 5, 2026.

Deliveroo

UK Government Digital and Data Profession

Canva

Zalando