u/SnoringSleepyHead

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I’ve been unemployed for the last 2 months due to a layoff, so I’m feeling the pressure to find something quickly. Yesterday, I had a technical SQL interview with an e-commerce firm, and it was an absolute nightmare—not because of the questions, but because the interviewer was completely lost.

For the first question, my solution passed all of their test cases. Despite this, he kept insisting the test cases "weren't complete." It became incredibly obvious that he had exactly one sample solution in front of him and refused to accept any other approach. At one point, he even got confused trying to explain the difference between an inner join and a left join.

By the time we got to the second question, it was clear he hadn’t even read it before the interview. He just copy-pasted it into the environment and immediately threw out a hint. Within 15 seconds, I had to point out that his hint was completely wrong. To his credit, he agreed, but the vibe was already ruined.

I really need this job, but this experience was incredibly frustrating. How do you all handle interviewers who are rigid, unprepared, or technically incorrect without coming across as argumentative or arrogant?

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I’ve been unemployed for the last 2 months due to a layoff, so I’m feeling the pressure to find something quickly. Yesterday, I had a technical SQL interview with an e-commerce firm, and it was an absolute nightmare—not because of the questions, but because the interviewer was completely lost.

For the first question, my solution passed all of their test cases. Despite this, he kept insisting the test cases "weren't complete." It became incredibly obvious that he had exactly one sample solution in front of him and refused to accept any other approach. At one point, he even got confused trying to explain the difference between an inner join and a left join.

By the time we got to the second question, it was clear he hadn’t even read it before the interview. He just copy-pasted it into the environment and immediately threw out a hint. Within 15 seconds, I had to point out that his hint was completely wrong. To his credit, he agreed, but the vibe was already ruined.

I really need this job, but this experience was incredibly frustrating. How do you all handle interviewers who are rigid, unprepared, or technically incorrect without coming across as argumentative or arrogant?

I have been laid off since last 6 months. Somehow received an interview for Google DS.

While I am strong in product metrics and SQL, my statistics and A/B Testing is very shaky.

What should I concentrate on for the initial 2 interviews? The stats and experimentation portion seems like a lot and I do not know how deeply I need to study each of the topics.

Round 1

- Measurement and Experiments

- Coding in SQL, Applied Analysis

Below is what is given by Google on prep materials

Modeling

The interviewers will want you to demonstrate experience with supervised and unsupervised methods to classify, categorize, and predict business matters.

Be ready for questions on the following topics: regression (linear, logistic), Bayesian and related methods, clustering analysis, Monte Carlo methods, decision trees, gradient boosted trees, neural networks.

Example question: How would you build a model to [predict, categorize, explain] XYZ?

Experimentation

The interviewer will want to understand that you can leverage experimentation principles and causal inference techniques to estimate impact.

Be ready for questions on the following topics: experimental design and foundations (stratified sampling and blocking, factorial designs, power analysis and sample size), inference challenges (optional stopping and p-hacking, multiple testing problems, non-parametric tests, network effects and spillover, cluster randomization, novelty and primacy effects, selection bias), variance reduction and evaluation (CUPED, hierarchical modeling, proxy/surrogate metrics), causal inference (propensity score matching, instrumental variables, regression discontinuity design, synthetic controls, double ML, causal impact).

Example question: Design an A/B test to measure XYZ [model, feature, change]. If an A/B test were not possible to run, how would you estimate the impact?