Junior Quantitative Analyst Data Analyst Interview Questions

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you are given a discrete probability distribution of children, what is the probability a random women you meet on the street has a sister? Two variables x1 and x2. They are correlated but aren't the same. X3 = X1-X2 and X4 = X1+X2. What are the coefficients for x1 and x2 if you train logit for x3 and x4 1000 ad videos, 1000 human raters Assess the quality of videos, 100 randomly selected videos to each rater, Rate video between 1 (bad) and 10 (good) quality. How would you rate these? What are the pros and cons of your strategy? clustered statistical modeling question about how you would set data up for this model and what model you would use.
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Quantitative Analyst

Interviewed at Google

4.4
Jan 16, 2022

you are given a discrete probability distribution of children, what is the probability a random women you meet on the street has a sister? Two variables x1 and x2. They are correlated but aren't the same. X3 = X1-X2 and X4 = X1+X2. What are the coefficients for x1 and x2 if you train logit for x3 and x4 1000 ad videos, 1000 human raters Assess the quality of videos, 100 randomly selected videos to each rater, Rate video between 1 (bad) and 10 (good) quality. How would you rate these? What are the pros and cons of your strategy? clustered statistical modeling question about how you would set data up for this model and what model you would use.

First onsite interviewer basically asked me some R questions -- how to load data, how to compute some group-level summary statistics. Second onsite interviewer asked me some basic stats questions -- interpreting coefficients, explaining good vs. bad dimension reduction approaches to a "layperson", then asked an applied question about evaluating two models used in Google search. Third onsite interviewer asked to compare two estimators (bias/consistency/efficiency), and how to evaluate results of a survey. Fourth onsite interviewer asked a stats question about optimal sequential behavior facing draws from an offer distribution without recall, then moved on to building a large-scale prediction model for a zero-inflated phenomenon at Google.
avatar

Quantitative Analyst

Interviewed at Google

4.4
Apr 3, 2017

First onsite interviewer basically asked me some R questions -- how to load data, how to compute some group-level summary statistics. Second onsite interviewer asked me some basic stats questions -- interpreting coefficients, explaining good vs. bad dimension reduction approaches to a "layperson", then asked an applied question about evaluating two models used in Google search. Third onsite interviewer asked to compare two estimators (bias/consistency/efficiency), and how to evaluate results of a survey. Fourth onsite interviewer asked a stats question about optimal sequential behavior facing draws from an offer distribution without recall, then moved on to building a large-scale prediction model for a zero-inflated phenomenon at Google.

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