Live coding

R Interview Copilot

R interviews are analyst interviews: the code is a means to an answer, and the answer has to survive a question about how the data was shaped.

The round

What a R interview actually looks like

Data science and biostatistics loops run R rounds against a small data frame, often shared as a screenshot rather than a file. The questions escalate from filtering and grouping to reshaping and joins, then to something statistical — which test, which assumption, what the p-value does and does not tell you. The statistical question is usually where the round is decided, and it is frequently posed as a flawed analysis you are asked to critique rather than a calculation you are asked to perform.

What you get back

Answers pick one dialect and stay in it: tidyverse pipelines when the round is tidyverse, base R when it is not, rather than mixing both in one block. Grouped operations state what they are grouping by and what they return. For statistical questions the answer names the assumptions before the method, because an interviewer is listening for whether you check them.

Example prompts

Questions people are actually asked

Send the transcript straight to the coding surface, or snip the problem off the screen.

  • Reshape this wide data frame to long and explain the key columns.

  • Which test applies here, and what does it assume?

  • Why does this join produce more rows than either input?

Where candidates lose points

R-specific traps

Ignoring NA propagation

Aggregations return NA unless you say otherwise, and a candidate who does not notice has reported a wrong number confidently.

Factors as strings

Factor levels persist after filtering and sort in level order rather than alphabetically, which quietly changes both plots and joins.

Reporting significance without effect size

A p-value with no effect size or interval is the answer most likely to draw a follow-up you cannot recover from.

Three surfaces

One workspace, three kinds of round

Chat

Behavioral rounds and the “tell me about a time” half of a technical screen, in your own voice.

Live coding

A structured solution with the reasoning attached, so you can talk through the code while you write it.

System design

Architecture answers with the diagram rendered inline, not described in prose.

Choosing a model

Statistical reasoning rewards depth over speed, so GPT-5.4 or Claude Opus 4.6 on the coding surface is the right trade here. The region-snip capture is especially useful in R rounds, since the data frame is usually on screen rather than in a file you can read.

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