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Lyft Interview Questions

Lyft operates a peer-to-peer marketplace for on-demand ridesharing in the United States and Canada

Lyft operates a peer-to-peer marketplace for on-demand ridesharing in the United States and Canada

Overview

Lyft Interview Guides

A/B Testing

Experiment Validity

Button AB Test

A/B Test Power Size

Network Experiment Design

ETA Experiment

Probability

First to Six

500 Cards

Raining in Seattle

Found Item

Given three uniform(0,4) random variables, what is the probability that the median of them is greater than 3?

Median Probability

Product Sense & Metrics

WAU vs Open Rates

Revenue Retention

Uber Eats Success

Increased Cancellations

Docs Metrics

Business Case

How to boost presence in high-demand city areas

Incentive Scheme

Decreasing Ride Costs

Machine Learning

One Million Rides

Building a model to predict if a driver on Uber will accept a ride request or not

Ride Requests Model

Challenge

How would you explain what a p-value is to someone who is not technical?

What does a p-value in a statistical test represent?

What does a p-value in a statistical test represent?

P-value to a Layman I

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

P-value to a Layman II

P-value to a Layman

Statistics

Let’s say that you work at a B2B SAAS company that’s interested in testing the pricing of different levels of subscriptions.

Your project manager comes to you and asks you to run a two-week-long A/B test to test an increase in pricing.

How would you approach designing this test? How would you determine whether the increase in pricing is a good business decision?

Testing Price Increase

A team wants to A/B test multiple different changes through a sign-up funnel.

For example, on a page, a button is currently red and at the top of the page. They want to see if changing a button from red to blue and/or from the top of the page to the bottom of the page will increase click-through.

How would you set up this test?

Your team wants to run an AB test on the color (red or blue) and position (top/bottom of the page) of a button that links to a promotion.

How many different variants of the test should you run to see the effect that a red button has on the bottom of the page, if currently the button is blue and on the top of the page.

Your team wants to run an AB test on the color (red or blue) and position (top/bottom of the page) of a button that links to a promotion.

How many different variants of the test should you run to see the effect that a red button has on the bottom of the page, if currently the button is blue and on the top of the page.

A/B Test Variants

Let’s say we want to launch a re-design of a landing page to improve the click-through rate. We can do this by implementing an AB test.
Given that we launch an AB test, how would you infer if the results of the click-through rate were statistically significant or not?

How can you accurately conclude if the results of an A/B test, conducted to evaluate the effectiveness of a landing page redesign, are statistically significant?

How can you accurately conclude if the results of an A/B test, conducted to evaluate the effectiveness of a landing page redesign, are statistically significant?

Statistically Significant Test

Precisely ascertain whether the outcomes of an A/B test, executed to assess the impact of a landing page redesign, exhibit statistical significance.

Let’s say that your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value.

How would you assess the validity of the result?

Let’s say you are working on Google Docs. A product manager comes to you and asks how the product is doing. 

What are the top five metrics that you would start tracking to understand the health of Google Docs?

Let’s say you want to test the close friends feature on Instagram Stories.

How would you make a control group and test group to account for network effects?

What could be a potential risk when Facebook segments the metrics of the user interface change by market or demographic groups?

What could be a potential risk when Facebook segments the metrics of the user interface change by market or demographic groups?

Network Experiment Design I

What is the primary metric that Facebook should monitor if it decides to make the user interface of its posting feature more like Instagram's?

What is the primary metric that Facebook should monitor if it decides to make the user interface of its posting feature more like Instagram's?

Network Experiment Design II

If Facebook changes its user interface to mimic Instagram's, which adverse effect should they anticipate and monitor?

If Facebook changes its user interface to mimic Instagram's, which adverse effect should they anticipate and monitor?

Network Experiment Design III

Let’s say you’re analyzing an AB test that has both a test group and a control group.

<ol>
<li>How do you calculate the sample size necessary for an accurate measurement?</li>

<li>Let’s say that the sample size is similar and sufficient between the two groups. In order to measure very small differences between the two, should the power get bigger or smaller?</li>
</ol>

Let’s say we’re testing a new UI with the goal to increase conversion rates. We test it by giving the new UI to a random subset of users.

The test variant wins by 5% on the target metric. What would you expect to happen after the new UI is applied to all users? Will the metric actually go up by ~5%, more, or less?

Note: Assume there is no novelty effect.

New UI Effect

Let’s say you’re interning at a fintech startup that’s building a platform for online games of chance. During testing, one of your simulations flips a coin 10 times and gets 8 tails and 2 heads.

How would you determine if the coin is fair, and what statistical approach would you use to support your conclusion?

How would you assess if a coin is fair after observing 8 tails in 10 flips?

Fair Coin

Let’s say you have to analyze the results of an AB test.

One variant of the AB test has a sample size of 50K users and the other has a sample size of 200K users.

Given the unbalanced size between the two groups, can you determine if the test will result in bias towards the smaller group?

Given an AB test where one variant has a sample size of 50K users and the other has a sample size of 200K users, what is the likely effect of the unbalanced sizes on the test results?

Given an AB test where one variant has a sample size of 50K users and the other has a sample size of 200K users, what is the likely effect of the unbalanced sizes on the test results?

Sample Size Bias

In an A/B test, how can you check if assignment to the various buckets was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

Random Bucketing

You are about to get on a plane to Seattle. You want to know if you should bring an umbrella. You call 3 random friends of yours who live there and ask each independently if it’s raining. Each of your friends has a 2⁄3 chance of telling you the truth and a 1⁄3 chance of messing with you by lying. All 3 friends tell you that “Yes” it is raining.

What is the probability that it’s actually raining in Seattle?

What is the main difference between the Frequentist and Bayesian methods of probabilistic analysis?

What is the **main** difference between the Frequentist and Bayesian methods of probabilistic analysis?

Frequentist Vs Bayesian Analysis

Let’s say you work at an eCommerce startup. You run an A/B test on the company’s checkout product page with the hypothesis that surfacing free shipping will increase conversions.

The experiment group specifies whether the product qualifies for free shipping or not. In the control group, there is no specification of free shipping.

Let’s say we run the experiment for two weeks and get these results.

Control:

<ul>
<li>3056 page visits</li>
<li>1413 conversions</li>
<li>46% conversion</li>
</ul>

Experiment:

<ul>
<li>2947 samples</li>
<li>1533 conversions</li>
<li>52% conversion</li>
</ul>

How would you evaluate the results and if the test was successful or not?

Free Shipping Mention Test

What are some effective ways to make data more accessible to non-technical people?

Demystifying data for non-technical users through visualization and clear communication

Accessible Data

Data Viz & Interpretation

Let’s say that you’re a data scientist on the engagement team. A product manager comes up to you and says that the weekly active users metric is up 5% but email notification open rates are down 2%.

What would you investigate to diagnose what’s happening?

Email Open Rate

Three zebras are chilling in the desert. Suddenly a lion attacks.
Each zebra is sitting on a corner of a triangle with sides of equal length.
Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?

Three zebras are chilling in the desert. Suddenly a lion attacks.

Each zebra is sitting on a corner of a triangle with side of equal length. Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?

Three zebras are chilling in the desert. Suddenly a lion attacks.

Each zebra is sitting on a corner of a triangle with side of equal length.  Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?



Three Zebras

Brainteasers

We want to determine if Uber Eats has a net positive value for the company Uber.

How would you measure the success of Uber Eats?

If Uber wants to evaluate the customer loyalty and repeat business on Uber Eats, which of the following metrics would be the most relevant?

If Uber wants to evaluate the customer loyalty and repeat business on Uber Eats, which of the following metrics would be the most relevant?

Uber Eats Success I

Which among the following metrics would be most indicative of the operational efficiency of Uber Eats?

Which among the following metrics would be most indicative of the operational efficiency of Uber Eats?

Uber Eats Success II

Which among the following metrics would be most critical in evaluating the overall profitability of Uber Eats for Uber?

Which among the following metrics would be most critical in evaluating the overall profitability of Uber Eats for Uber?

Uber Eats Success III

Let’s say you work at a food delivery company.

How would you measure the effectiveness of giving extra pay to delivery drivers during peak hours to meet the demand from consumers?

Extra Delivery Pay

Uber Rider deals with huge amounts of data but at Uber Fleet, the amount of data for experimentation is rather low. Let’s say you run an AB test for Uber Fleet and find out that the distribution is not normal.

What kind of analysis would you run and how would you measure which variant won?

Which of the following is NOT an acceptable way to deal with AB testing on a non-normally distributed population?

Which of the following is NOT an acceptable way to deal with AB testing on a non-normally distributed population?

Non-Normal AB Test

Non-Normal AB Testing

To improve customer experience on Uber Eats, what key parameters would you focus on improving?

Delivering an exceptional customer experience by focusing on key customer-centric parameters

Uber Eats Customer Experience

Amy and Brad take turns in rolling a fair six-sided die. Whoever rolls a “6” first wins the game. Amy starts by rolling first.

What’s the probability that Amy wins?

Amy and Brad take turns in rolling a fair six-sided die. Whoever rolls a “6” first wins the game. Amy starts by rolling first.

What’s the probability that Amy wins?

Imagine a deck of 500 cards numbered from 1 to 500. If all the cards are shuffled randomly and you are asked to pick three cards, one at a time, what’s the probability of each subsequent card being larger than the previous drawn card?

Imagine a deck of 2000 cards numbered from 1 to 2000. If all the cards are shuffled randomly and you are asked to pick three cards, one at a time, what’s the probability of each subsequent card being larger than the previously drawn card?

Imagine a deck of 2000 cards numbered from 1 to 2000. If all the cards are shuffled randomly and you are asked to pick three cards, one at a time, what's the probability of each subsequent card being larger than the previously drawn card?

2000 cards

Let’s say we want to build a new algorithm for Lyft Line.

How should we test it, measure success of the test, and eventually roll it out?

Building Lyft Line

You work as a data scientist on a ride sharing marketplace.

<ol>
<li>What metrics would you look at to determine the demand for rides at any point?</li>

<li>What metrics would tell you if there is high demand and low supply? How can you determine the threshold for when there’s too much demand?</li>
</ol>

As a data scientist in a ride sharing marketplace, which metrics could help determine the demand for rides at any point?

As a data scientist in a ride sharing marketplace, which metrics could help determine the demand for rides at any point?

Demand Metrics I

In the context of a ride sharing marketplace, which situation would indicate a high demand and low supply?

In the context of a ride sharing marketplace, which situation would indicate a high demand and low supply?

Demand Metrics II

How would you identify supply and demand mismatch in a ride sharing market place?

Demand Metrics

Let’s say we’re given a biased coin that comes up heads 30% of the time when tossed.

What is the probability of the coin landing as heads exactly 5 times out of 6 tosses?

Biased five out of six

Let’s say we have a very naive advertising platform. There is an audience of size A and a limited amount of impressions B.

Each of the impressions goes to just one user, defined at random. Every user in the audience has the same random chance of receiving each impression. 

<ol>
<li>Compute the probability that a user has exactly 0 impressions. </li>

<li>What’s the probability that every person has at least 1 impression?</li>
</ol>

Impression Reach

Let’s say you work at a company developing a new ride-sharing app.

How would you design a database that could record rides between riders and drivers?

What would the schema of the tables look like and how would they join together?

Design a database for a ride-sharing app.

Ride-Sharing App Schema

Data Modeling

Amazon has a warehouse system where items on the website are located at different distribution centers across a city. Let’s say in one example city, the probability that a specific item X is available at warehouse A or warehouse B are 0.6 and 0.8 respectively.

Given that you’re a customer in this example city and the items are only found on the website if they exist in the distribution centers, what is the probability that the item X would be found on Amazon’s website?

Given three random variables independently and identically distributed from a uniform distribution of 0 to 4, what is the probability that the median of them is greater than 3?

How can we calculate the probability that the median of three random variables from a uniform distribution of 0 to 4 is greater than 3?

How can we calculate the probability that the median of three random variables from a uniform distribution of 0 to 4 is greater than 3?

Calculate Moving Average	SQL	Easy
Predict Customer Churn	Machine Learning	Medium
A/B Test Significance	Statistics	Medium
Optimize Query Performance	SQL	Hard
Feature Importance Analysis	Machine Learning	Medium
Clean Missing Data	Python	Easy
Neural Network Architecture	Deep Learning	Hard
Calculate Cohort Retention	SQL	Medium
Bayesian Probability	Statistics	Easy
Recommend Similar Products	Machine Learning	Hard

Lyft Interview Questions

Overview

Lyft Interview Guides

Challenge

Lyft Interview Questions

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Discussion & Interview Experiences

Discussion & Interview Experiences