Experimentation branch · five minutes
Why peeking inflates false positives
A PM checks the experiment dashboard every morning and wants to ship as soon as p < 0.05. What is the main problem with this policy?
Interview field notes · issue 01
Diagnose a funnel, design an incrementality test, pick the north-star metric, rank the roadmap, or prove an AI agent works. Each question is graded against a model answer written the way strong candidates answer.
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Uplift is an interview-practice platform for analytics, experimentation, product and AI roles. You answer interview-style questions in the format the interview uses: SQL against sample tables, multiple choice, a computed number, or a written case. Each submission is graded against an answer key or rubric. Hints unlock one at a time, attempts are unlimited, and the model answer stays hidden until you ask for it. Read how grading and the leaderboard work.
Evidence from the product · example
Experimentation branch · five minutes
A PM checks the experiment dashboard every morning and wants to ship as soon as p < 0.05. What is the main problem with this policy?
01 / 08
Window functions, joins, funnels and event models under interview time pressure.
20 questions
02 / 08
Design, power, guardrails, peeking and readouts for online experiments.
18 questions
03 / 08
Metric trees, retention shapes, activation and diagnosing a drop.
21 questions
04 / 08
Distributions, intervals, regression intuition and error tradeoffs.
17 questions
Step 1
Choose from eight skill tracks, called branches, covering the work analysts, product managers and marketing teams are actually interviewed on.
Step 2
Run the query and inspect the rows it returns, pick the option, compute the number, or structure the case in prose. Unlimited attempts.
Step 3
Submissions return checks and pass/fail feedback; the model answer and its reasoning stay hidden until you ask to see them.
Free accounts get every non-premium question, attempt history, and the progress tree. Pro unlocks the harder company-style sets and full model write-ups.