lyft case study interview

Lyft Data Scientist Interview Guide

Back to Lyft

Introduction

Lyft, Inc. is a rapidly expanding ride-sharing company based in San Francisco, operating in 644 cities across the United States and 12 cities in Canada. Founded in 2012 as a part of a long-distance car-pooling business originally called Zimride, Lyft launched in Silicon Valley in 2013. The company has quickly spread, expanding from 60 US cities in April 2014 to over 300 by January 2017. Now, Lyft has grown to over 23 million users, with a billion recorded rides as of 2020.

Lyft generates millions of data points daily and needs to scale out its data science and research science capabilities. Hence, the dedicated data science and business intelligence department is tasked with leveraging the most advanced analytics, machine learning, and big data (using AWS S3/AWS EC2) tools in providing business models and insights .

The Data Science Role at Lyft

The data science capabilities at Lyft are split into three specific teams: Data Scientists, Research Scientists, and Machine Learning Engineers .

Data scientists are responsible for building an analytics infrastructure , creating models, and setting up dashboards for self-service analytics. Originally branded as data analysts, the data scientist role at Lyft is much more focused on analytics and being embedded with product managers to drive product decisions forward.

Research scientists at Lyft function more as traditional data scientists and ship production code to work on the core machine learning projects, such as the estimated ride time and the pricing of each ride. Lyft research scientists work a lot on the automation engines that run the Lyft app and product.

Lastly, machine learning engineers at Lyft focus on building the infrastructure needed to host the complicated models that the research scientists build.

Data science roles at Lyft are tailored specifically to teams in different products and features . The precise role and responsibilities will depend on the teams and products/features you are assigned to.

Whatever the teams you are working with or product/features your team is assigned to, the role of a data scientist at Lyft will span across business analytics, modeling, machine learning, and deep learning implementation.

Required Skills

Lyft has a culture of creating an “open, inclusive, and diverse environment where members are recognized for what they bring to the table” . Lyft prefers to hire highly qualified applicants with 3 years plus experience in data analysis and data visualization .

Other basic requirements for hiring at Lyft include:

• BA/BS in a quantitative field like statistics, economics, applied math, operations research, or engineering. Advanced degrees are preferred.
• 3+ years of industry experience in a data science or analytics role.
• Excellent data analysis, modeling, Python, and SQL language (MySQL, PostgreSQL, SqlServer, Oracle) skills - able to write structured and efficient queries on large data sets.
• Proficiency in Tableau, Power BI, or similar data visualization software.
• Very comfortable building new data tables using ETL logic: building, managing, and fixing entire enterprise data models.
• Proficiency in workflow management tools such as Airflow.
• Exceptional communication skills with the ability to present findings & recommendations targeted to the audience in question.

What kind of data science role?

There is dedicated data analytics and business intelligence department at Lyft, but depending on the teams and product you are assigned to, the job role and function may differ a little. Depending on the teams, the functions may include:

• Leveraging statistical modeling, machine learning, or data mining techniques to deliver actionable recommendations to CET leaders.
• Leveraging machine learning to automate tools to manage growth levers.
• Track and make reports on KPIs connected to central work streams through weekly, monthly & quarterly business reviews.
• Analyze the market-level impact of price changes across the marketplace.
• Work closely with product leads to build the most efficient tools, systems, and processes to manage pricing at scale.

Data science teams at Lyft include:

• Autonomous Vehicle
• Marketplace
• Dynamic pricing
• Growth team
• Rider experience
• Driver experience
• Airport experience

Lyft Data Scientist Interview Process

Lyft’s data science interview process starts with an initial phone screening with a hiring manager or HR, a take-home challenge (with usually 24 hours delivery time), or a technical screen. After successfully passing through both the take-home challenge and a 45-minute long technical interview (two technical interviews in some cases), it is followed by five or six one-on-one interviews on-site, now virtually due to covid-19.

Initial Screen

This interview is mainly exploratory and resume-based . The main focus here is on assessing your background, especially past experience, roles, and team dynamics , to determine if you are a potential fit. The initial screening is done via a phone call from an HR or a hiring manager.

See our guide to data science behavioral questions .

Technical Screen

The next step in the interview process is the technical interview phone screen with a data scientist. This interview lasts between 30 and 45 minutes. Lyft’s data science interview questions span the fundamentals of probability, statistics, machine learning, business case study, the definition of some operational KPIs, a walk-through of the maths from your hypothesis testing, and your technical/past project experiences.

The Take-Home Challenge

After completing the initial screening, you will receive a Lyft take-home challenge that you will have 24 hours to complete. Questions in the take-home challenge are case-study-based questions (ridesharing dataset), and they comprise both technical and business side problems. In this challenge, questions typically span across different topics, such as churn rate measurement, optimization (using machine learning), designing/experimentation for recommendations, and creating a comprehensive report about your assumptions, limitations, and conclusions.

Check out the Lyft take-home challenge on Interview Query.

On-site Interview

After passing the technical screen, the next scheduled interview in the process is the on-site interview. This process comprises five or six one-on-one rounds of interviews with a data scientist or a team manager, each lasting for approximately 45 minutes. This is a half-day interview process involving whiteboard coding, project discussion with team managers and data scientists, business case studies, and statistical concepts .

In general, the cumulative interview process will look like this:

• A presentation of the take-home data challenge– at this interview, the candidate is required to make a presentation of the take-home challenge submitted in an earlier part of the interview process.

Note: At this stage, you are expected to build a coherent story around your analysis while answering questions on what metrics you used and why you chose them.

• A business case study interview: questions in this interview are mainly open-ended, surrounding a real-life business case study. It is advisable to brush up on some of the unit economics metrics related to ridesharing at Lyft.
• Statistics and probability with a data scientist: questions here revolve around hypothesis testing, such as the classic “coin got x heads during y flips”. It pays to familiarize yourself with business applications of key concepts, their variants, and data manipulation using SQL.
• SQL/Python interview: this is a 45-minute-long interview with a data scientist that involves whiteboard coding in SQL or R/Python and algorithm.
• Core values/cultural fit interview with a product manager.

The interview process aims to assess your experience with analytical concepts and design skills in providing business impact insights . Remember to brush up on your knowledge of statistics and probability (A/B testing), experimental design, and the business applications of key statistical concepts.

Also, reading up on key economic metrics and KPIs, algorithms, and models will be helpful. Practice lots of SQL interview questions , as these can better prepare you for the technical aspects of the interview process.

Lyft Data Scientist Interview Questions

• Describe how to engineer the heatmap telling drivers where to go. How would you define which areas will have high demand next and whom do you want to go there?
• How do you model the impact of surge on demand and supply?
• Explain correlation and variance.
• Explain the best ways to achieve pool matching.
• How do you reduce churn on the supply side?
• What is the lifetime value of a driver?
• What are some of the different factors that could influence a rise in the average wait time for a driver?
• What optimization techniques are you familiar with, and how do they work on a basic level? How would you find the optimal price given a linear demand function? Take a derivative of a quadratic function.
• How do you draw a uniform random sample from a circle in polar coordinates?
• Find expectations of a random variable with a basic distribution. How would you construct a confidence interval?
• How would you estimate the probability of a user ordering a ride? What assumptions do you need in order to estimate this probability?

See more Lyft data scientist questions from Interview Query:

Lyft data scientist salary.

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How to Nail your next Technical Interview

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Top Lyft Interview Questions for Software Engineers and Developers

Last updated by Ashwin Ramachandran on May 30, 2024 at 05:53 PM | Reading time: 12 minutes

Lyft offers multiple technical positions for software engineers, developers, tech leads, and engineering managers. To ace technical Lyft interview questions, it is important to understand the crucial programming concepts. You must thoroughly prepare Lyft interview questions on system design, SQL, data science, algorithm, coding, and other software development topics.

Lyft provides opportunities to work on various complex, highly technical systems that have an immediate and profound impact on millions of people worldwide. Lyft is always on the lookout for exceptional engineers to join its expanding engineering team.

It is looking for professional software engineers who can assist with scalability issues, optimize the network of passengers and drivers, and make complex products clear and easy to understand. Practicing Lyft interview questions will help you prepare for your next technical interview.

If you are preparing for a tech interview, check out our technical interview checklist , interview questions page, and salary negotiation e-book to get interview-ready!

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Here's what we'll cover in this article:

• What Is the Lyft Interviews Process for Software Developers?

Lyft System Design Interview Questions and Answers

Lyft interview questions on coding and programming, lyft interview questions on data science.

• Behavioral Lyft Interview Questions

FAQS on Lyft Interview Questions

What is the lyft interview process for software developers.

You need to understand the Lyft interview process to prepare well for Lyft interview questions. Lyft interviews are typically divided into four stages: recruiter screening, technical phone screening, On-site, and team matching.

Round 1: Screening with Recruiters

The recruiter phone screen is quite simple, consisting mainly of questions based on your resume and suitability for the software engineer post. Then, the recruiter will guide you through the interview process at Lyft . It is a 30-minute conversation.

Round 2: Technical Phone Screen

In a technical phone interview, you need to spend one-hour answering technical questions with a Lyft software engineer. The questions on the technical phone screen are often less in-depth. However, they will cover any of the categories of questions discussed in the following section.

Round 3: On-site Interview

The Lyft software engineer On-site interview comprises four rounds:

• System Design Interview - You can either use a whiteboard or a laptop for these questions. It would help if you clarified with your recruiter beforehand. This is a 60-minute interview.
• Coding Interview - Interview for Computer Science fundamentals, including problem-solving, data structure, and algorithms. There are two coding rounds.
• Laptop Assignment - This assignment simulates the type of work you would do at Lyft day-in and day-out. You will have 90 minutes for this assessment.
• Behavioral Interview - This comprises behavioral and situational questions concerning your previous work experiences, which helps an interviewer predict your future behavior.

Round 4: Matching Teams

After completing the On-site interview, you will be matched with possible teams and have exploratory calls with the managers on those teams. These future meetings will be more like chats than interviews, where you may get to know the team. This round simulates the working environment and helps determine the mutual fit for the role.

Lyft system design interview questions include API, databases, and more. Lyft SQL interview questions form a major portion of these interviews. In a 60-minute interview, the hiring manager at Lyft asks you to design a large system relevant to Lyft's operations.

You can use Google Draw as it allows you to collaborate in real-time to create, edit, and share drawings online. The interviewers can view your work, and you can also chat with them to explain your concepts. This process involves developing a way to communicate your strategies, proposing an API, and modeling database tables.

You will be given two system design questions. Through these Lyft interview questions, the hiring manager checks:

• If your structure takes a systematic approach
• Does your approach cover all requirements?
• The feasibility, i.e., whether your answer is practical and could be implemented

Some common Lyft interview questions on System Design include:

Q1. Design a cab-hailing system from scratch

This Lyft interview question is very open-ended. Cab-hailing apps can have any number of features. You ought to distill the question down to 2-3 core features. Then design a system around those first. You can add more features later. The primary features can be:

• User (Rider) and Driver Profile
• The rider can hail a ride. A rider can find a nearby driver, and the driver can give a ride.

To prepare for System Design Lyft interview questions, practice and watch system design mock interviews. It would be best if you got familiar with Google Draw before the interview.

Q2. How would you build a tourist-friendly bicycle rental app?

This Lyft interview question aims at analyzing your understanding of the primary requirements of a tourist-friendly app design. The following features can be incorporated into a tourist-friendly bicycle rental app.

• Create a multilingual app that prompts the user to choose a language after installation.
• Every bike will be fitted with a GPS device, and the bikes will be displayed to the user in a map view.
• Payment in advance - Set up a payment wallet, a credit card, or a debit card.
• Activate the bicycle - Scan the QR code to unlock the bike, start the trip automatically and record and display the rider's time.
• Safety - Each bike will have a helmet affixed to it.
• Parking spaces will be displayed to app users to guarantee that bikes are parked in densely populated city sections.

Q3. Design a dashboard as Lyft's product manager to monitor the app's health.

Software engineers have to primarily deal with Lyft application and structure. This Lyft interview question is commonly asked in Lyft system design interview rounds. The dashboard will include the following:

Buyer Side:

• Number of new downloads
• Number of new first users
• Number of total active users
• Total distance driven

Driver Side:

• Number of new drivers onboarded
• Number of active drivers churn
• Distance driven per active driver
• Number of rides per active driver

Product-Related:

• Number of customer support calls/tickets
• Number of location sharing or safety feature usage rides
• Number of active drivers per MAU active user
• Number of app crashes

Q4. Create Lyft for deaf drivers.

Consider the following to answer this Lyft interview question:

• Drivers can text passengers before arrival, indicating their impairment and asking for their patience.
• If users wish to be dropped off somewhere different, they can send quick, personalized messages requesting that the driver drop them off somewhere else.
• When the driver's phone receives a message from a passenger, it will vibrate, and the screen will blink for a few seconds to grab the driver's attention.
• Passengers can spot the car using a brightly colored blinker and the license plate number.

There are two coding rounds in the Lyft interview. Lyft interview questions include Hackerrank and LeetCode type of questions.  

During the interview , a Lyft software engineer will present a problem. You will have to write an algorithm or program to solve the problem. You must practice problems on data structure and algorithms to ace Lyft coding interview questions.

Lyft Interview Questions on Array

• For a given array containing positive integers, write a code to return the sum of the elements of the array.
• For a given array of size N, write a code to print the reverse of the array.

Lyft Interview Questions on Strings

• Write a code to reverse the string without disturbing the individual words for a given string S.
• Write a code to remove successive duplicate characters recursively for a given string S.

Lyft Interview Questions on Algorithms

• For a given Directed Acyclic Graph, write a program that finds the topological sorting in the graph.
• Write a program to perform its vertical traversal for a given binary tree .

To practice coding problems for your next interview, check out coding problems with solutions.

If you're applying to a data scientist position at Lyft, you can expect a round dedicated to testing your data science fundamentals. Here are a couple of sample Lyft Interview Questions on Data Science:

• How would you effectively represent data with multiple dimensions?
• Using multiple regression, how would you validate a model you created to generate a predictive model of a quantitative outcome variable?

Behavioral Lyft Interview Questions for Practice

Here are a few behavioral and situational Lyft interview questions for practice.

• Determine the root reason for a 10% drop in rides?
• What drives your interest in this position at Lyft?
• Assume Lyft is considering entering the delivery market. What strategy should it take to this concept?
• How can there be enough drivers to handle the number of deliveries at any particular time and location?
• Build a car-sharing network for persons with disabilities?
• Lyft plans to introduce Shared Saving rides. What criteria will you take into account when determining passengers willing to pay? What experiments will you conduct to put your notions to the test?
• Create the Lyft app for the visually impaired.
• The ride scheduling capability is one of the ideas added to your backlog. Analyze this scheduling feature from a product standpoint and suggest whether to move on with the implementation stage.
• What are your relevant previous experiences for the role?
• How would you handle team members who do not work up to their full potential?
• Do you care about impact and action-oriented solutions?
• How do your experiences align with Lyft's values?

Q1. How to prepare for the Lyft interview questions?

To prepare well for Lyft interview questions, you must research the primary fundamentals of the company. Practice programming for Lyft coding interview questions. It would help if you were prepared to use standard input and output in the scripting language.

Q2. What are Byteboard Lyft interview questions?

The Byteboard Lyft interviews are used in place of one or more of your pre-on-site technical interviews. Byteboard Lyft interview questions concentrate on core software engineering skills through practical, real-world problems.

These include technical aspects such as algorithms, data science, SQL, system design, and more. This gives a thorough overview of your software engineering abilities and allows employers to make confident judgments about which individuals to bring on board.

Q3. What types of Lyft interview questions are asked in software engineer interviews?

Lyft interview questions for software engineers cover four categories: programming fundamentals, system design, practical coding questions, and behavioral questions.

Q4. What topics are important for Lyft interview questions for mobile software engineers?

Mobile software engineers must prepare SQL, React, JVM, Ruby, and other Android technologies for Lyft interview questions . Practice coding and advanced questions on programming languages, especially Python and Java.

Q5. How many rounds are there in the Lyft interview ?

The interview process at Lyft mainly has three rounds. Round 1 consists of a phone interview with a recruiter. Round 2 consists of two case study interviews with the Product team. Round 3 consists of two case study interviews plus a behavioral interview with the product team. There were prep calls, videos, and articles to help candidates prepare in between rounds.

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Lyft Data Scientist Interview Guide

Are you looking for data science roles in Lyft? Here's a guide to help you out!

The role of a Lyft Data Scientist

Why consider data science role at lyft.

Lyft is a transportation network company that provides ride-sharing services through a mobile app in over 600 cities in the United States and Canada. They offer a range of ride options, as well as bike and scooter-sharing services in select cities. The company's mission is to provide safe, convenient, and affordable transportation options for everyone, and they have introduced various initiatives, such as carpooling and discounts, to achieve this goal while also working to reduce their carbon footprint.

Lyft uses data science to improve its ride-sharing services in various ways. This includes demand prediction, pricing optimization, route optimization, fraud detection, and user experience. By leveraging data science, Lyft can allocate resources efficiently, offer competitive pricing, reduce wait times, ensure the safety of its passengers and drivers, and provide a better user experience.

Applying for a Data Scientist Job in Lyft

• Visit the Lyft Careers Service
• Prepare your application materials: You will need to submit a resume, cover letter, and any relevant project samples or portfolio. Make sure your materials are tailored to the specific position you are applying for and highlight your relevant skills and experience.
• Submit your application
• Follow up: After submitting your application, it is a good idea to follow up with a quick email or call to ensure that your application was received and to express your continued interest in the role.

The interview process for a data scientist role at Lyft may vary depending on the specific role and the department you are applying for. However, it may typically involve the following steps:

• Phone screen: The first step in the interview process may be a phone screen with a recruiter or hiring manager. This is typically a brief conversation to assess your interest in the position and to discuss your background and qualifications.
• Technical interview: The next step is usually a technical interview, which may be conducted over the phone, video conferencing, or in person. This interview may focus on topics such as statistical modelling, machine learning, data analysis, and coding skills. You may be asked to solve coding problems, answer technical questions, or work through hypothetical business problems.
• On-site interview: If you pass the technical interview, you may be invited to an on-site interview. This typically involves a full day of interviews with multiple team members, including data scientists, data analysts, and hiring managers. You may be asked to work through additional coding problems or case studies, as well as behavioural and cultural fit questions.

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Lyft data scientist - phone screening.

The phone screening process for a data scientist position at Lyft is typically the first step in the interview process. The purpose of the phone screen is to determine if you meet the basic qualifications for the position and to learn more about your background and experience. Here are some of the things you can expect during the phone screen:

• Overview of the role: The recruiter or hiring manager will likely provide you with an overview of the data scientist position, the responsibilities, and the requirements.
• Assessment of qualifications: The recruiter or hiring manager may ask you questions related to your technical skills, experience in data science, and education. They may also ask about your experience with specific tools and programming languages commonly used in data science, such as Python, R, and SQL.
• Behavioural questions: In addition to technical questions, the recruiter or hiring manager may ask behavioural questions to assess your fit for the position and the Lyft culture. For example, they may ask you to describe a time when you had to work with a difficult team member or how you handle ambiguity and uncertainty.
• Questions for the interviewer: You will have the opportunity to ask questions about the position, the team, or the company culture. It is important to prepare thoughtful questions to show your interest in the position and to learn more about the company.

Overall, the phone screening process for a data scientist position at Lyft is typically brief, lasting around 30 minutes to an hour. The recruiter or hiring manager will use this time to assess your qualifications, experience, and fit for the position. If you pass the phone screen, you will move on to the next step in the interview process, which may be a technical interview.

Interview Questions

• Tell me about your experience with data analysis and statistical modelling.
• Can you describe your experience with Python, R, SQL, or other programming languages commonly used in data science?
• Have you ever worked with large data sets? If so, how did you approach the data cleaning and analysis process?
• Tell me about a time when you had to solve a complex data problem. How did you approach the problem, and what tools did you use?
• How do you stay up to date with developments in the field of data science?
• How do you handle ambiguity and uncertainty when working on a project?
• Can you describe your experience with A/B testing, and how you designed and implemented experiments to test a hypothesis?
• What kind of projects have you worked on in the past that you think are most relevant to the position you're applying for?
• Tell me about a time when you had to work with a difficult team member or stakeholder. How did you handle the situation?
• What motivates you to work in the field of data science, and why are you interested in this particular position at Lyft?

Lyft Data Scientist - Technical Interview

The technical interview is an important part of the Lyft data scientist interview process, as it is designed to assess your technical skills and problem-solving abilities. Typically, the technical interview is conducted via a video call or in-person interview and consists of a series of technical questions related to data analysis, statistics, machine learning, and programming. It is important to be well-prepared for the technical interview by reviewing the job description and studying relevant topics in data science, statistics, and machine learning. It is also important to demonstrate your problem-solving abilities by walking the interviewer through your thought process and explaining your reasoning as you work through the questions. Finally, be sure to communicate clearly and confidently, and do not be afraid to ask questions or seek clarification if you're unsure about something.

• Can you explain the difference between supervised and unsupervised learning?
• How would you approach feature selection for a given data set, and what factors would you consider?
• Can you walk me through your process for data cleaning and preparation, and how you would deal with missing or corrupted data?
• How would you design and implement a recommendation system for a ride-sharing service like Lyft?
• How would you approach optimizing the pricing strategy for Lyft, considering various factors such as demand, supply, time of day, and weather conditions?
• Can you explain the concept of overfitting and how you would prevent it when training a machine learning model?
• How would you design and implement an A/B test to evaluate a new feature on the Lyft app?
• Can you describe your experience with time series analysis, and how you would use it to forecast demand for Lyft's ride-sharing services?
• How would you detect and prevent fraud in a ride-sharing service like Lyft?
• Can you explain the concept of bias and how you would address it when developing a machine learning model?

Practice for your Lyft DS interview

Read these articles, lyft data scientist - on-site interview.

The onsite interview is the final stage of the Lyft data scientist interview process, and is typically conducted at the Lyft office. The onsite interview is designed to assess your technical skills and cultural fit with the company, as well as to give you a better sense of what it is like to work at Lyft.

The onsite interview usually consists of several rounds, including technical interviews, a behavioural interview, and possibly a presentation or coding exercise. Here is a breakdown of what you can expect:

• Technical Interviews: The technical interviews are similar to the ones in the phone screening, but are more in-depth and may involve coding exercises. The interviewers will ask you questions related to data analysis, statistics, machine learning, and programming, and will assess your problem-solving skills and ability to work through complex technical challenges.
• Behavioural Interview: The behavioural interview is designed to assess your cultural fit with Lyft, as well as your ability to work effectively in a team. The interviewer will ask you questions about your work experience, your approach to problem-solving, and your communication and collaboration skills.
• Presentation or Coding Exercise: Depending on the position you are applying for; you may be asked to give a presentation or complete a coding exercise. The presentation may involve presenting your findings from a data analysis project, while the coding exercise may involve writing code to solve a specific problem related to data analysis, machine learning, or programming.

Throughout the onsite interview, it is important to be well-prepared, professional, and engaged. Be sure to review the job description and the Lyft website to learn more about the company and its culture, and be prepared to discuss your relevant work experience and skills. You should also be prepared to demonstrate your problem-solving abilities and technical skills, and to communicate clearly and confidently with your interviewers. Finally, be sure to ask questions and show your interest in the position and the company.

• How would you approach modelling demand for Lyft's ride-sharing service in a new market?
• Can you explain how you would design a machine learning algorithm to predict the likelihood of a passenger cancelling their ride?
• What are some of the biggest challenges you have faced when working with large data sets, and how did you overcome those challenges?
• Can you walk me through the steps you would take to clean and pre-process a data set before conducting analysis?
• Can you explain the differences between regularization techniques such as L1 and L2, and when you might use one over the other?
• Can you tell me about a time when you had to communicate complex technical concepts to a non-technical stakeholder? How did you approach the situation, and what was the outcome?
• How do you prioritize and manage your work when you have multiple projects with competing deadlines?
• How do you handle situations where you don't have all the information you need to solve a problem?
• Can you give an example of a time when you had to work collaboratively with team members who had different backgrounds or skill sets than you?
• How do you keep up with the latest developments and trends in data science and machine learning?
• Analyze a data set and present your findings to the interviewers.
• Write code to solve a specific problem related to data analysis or machine learning.
• Design and present a machine learning algorithm to solve a real-world problem related to the ride-sharing industry.

Tips to stand out in Lyft DS interviews

• Demonstrate strong technical skills: Lyft values technical expertise, so be sure to demonstrate your knowledge of statistical analysis, machine learning, and programming languages such as Python and R. Be ready to discuss specific projects you have worked on that highlight these skills.
• Showcase your communication skills: Data scientists must be able to communicate complex findings to a variety of audiences. Prepare to explain your findings and methods in clear, concise language. Additionally, be ready to ask thoughtful questions to show your understanding of the business needs of Lyft.
• Emphasize your experience with large datasets: Given the scale of Lyft’s operations, experience with large datasets is a must. Be prepared to discuss your experience working with big data, as well as your knowledge of data warehousing and data management.
• Highlight your problem-solving abilities: Lyft is looking for data scientists who can solve complex problems. Be prepared to discuss how you have tackled difficult data-related issues in the past, as well as your ability to think creatively to find solutions.
• Show your passion for the company: Companies like Lyft want to see that candidates are truly interested in the work they are doing. Do your research on Lyft’s mission and values, and be prepared to discuss how your skills and experience align with those values.
• Be prepared for technical questions and coding challenges: Expect to be tested on your technical skills. Lyft may ask you to write code or solve a technical problem on the spot, so practice your coding skills in advance.
• Be familiar with the industry : Show that you are familiar with the latest developments and trends in the ride-sharing industry. Be ready to discuss how Lyft can improve its service through the use of data analysis.
• Show that you are a team player: Collaboration and teamwork are essential in any data science role. Be prepared to discuss how you have worked with cross-functional teams and how you approach working with others to solve complex problems.

Roles and Responsibilities of Lyft Data Scientists

As a data scientist at Lyft, you would be responsible for driving data-driven decision-making across the company. Your key roles and responsibilities would include:

• Conducting data analysis: You would be responsible for collecting, analysing, and interpreting large and complex datasets. You would use statistical techniques and machine learning algorithms to identify patterns and insights that help drive business decisions.
• Developing models: You would develop models to predict and forecast trends, analyse customer behaviour, and optimize the efficiency of the company's operations. You would use your knowledge of machine learning and statistical modelling to create accurate and efficient models that can be used to improve the company's performance.
• Collaborating with cross-functional teams: You would work closely with other departments and stakeholders, such as product management, engineering, and marketing, to provide data insights and recommendations. You would work collaboratively to ensure that all teams have the information they need to make data-driven decisions.
• Designing experiments: You would design experiments to test hypotheses and evaluate the impact of new features or changes to the product. You would use statistical methods to analyse the results and draw conclusions that can be used to guide decision-making.
• Communicating results: You would be responsible for communicating your findings to various stakeholders in the company. You must be able to translate complex data analysis into easily understandable insights that can be used to make informed decisions.
• Staying up-to-date with the latest technologies: You would be responsible for researching and experimenting with new techniques and technologies to improve the efficiency and accuracy of your work. Data science is a rapidly evolving field, and you would need to stay current with the latest tools and technologies.

Overall, as a data scientist at Lyft, you would play a critical role in helping the company make data-driven decisions that improve the customer experience, optimize operations, and drive business growth.

Skills expected of Lyft Data Scientists

We looked at more than 60 data scientist job listings on Lyft’s website and consolidated the most common requirements.

Technical Requirements:

As a data scientist at Lyft, you would be expected to have a strong technical background and the ability to work with large and complex datasets. Some of the technical requirements for you may include:

• Strong proficiency in programming languages such as Python or R, and familiarity with SQL.
• Expertise in data analysis, statistical modelling, and machine learning techniques.
• Experience with big data technologies such as Hadoop, Spark, and Hive.
• Strong knowledge of data visualization tools such as Tableau or D3.js.
• Ability to work with distributed systems and cloud-based platforms such as AWS or Google Cloud.
• Familiarity with software development practices such as version control, continuous integration, and automated testing.
• Good understanding of data structures and algorithms.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.

In addition to these technical requirements, you would be expected to have good communication skills, be able to work in a team, and have a strong business acumen. You should also be curious, self-motivated, and always willing to learn and adapt to new technologies and techniques.

Pay ranges for Lyft Data Scientists

Lyft data scientists' pay scale can vary depending on factors such as experience, location, and education. According to Glassdoor, the average base pay for a data scientist at Lyft is around $136,000 per year in the United States. However, this can range from approximately $115,000 per year to over $160,000 per year, depending on the factors mentioned above. Additionally, Lyft may offer additional benefits and compensation, such as bonuses, stock options, and health benefits.

Practice with a Lyft DS - spend less than 0.1% of the salary you'd earn once you get the job!

The data scientist interview process at Lyft consists of several stages: application, phone screen, technical assessment, technical and behavioural interviews, and an on-site interview. The process aims to evaluate the candidate's technical skills, problem-solving abilities, communication skills, and fit with the company culture. Good luck!

Frequently Asked Questions

What kind of questions can I expect in a Lyft Data Scientist job interview?

What kind of technical questions can I expect in a Lyft Data Scientist job interview?

How can I prepare for a behavioral interview question?

Are there any tips for acing a Lyft Data Scientist job interview?

Is the Lyft Data Scientist interview guide suitable for entry-level candidates?

How long does it take to prepare for a Lyft Data Scientist job interview using the interview guide?

Relevant interview guides

Lyft PM interview guide (questions, process, prep)

Lyft product manager interviews are difficult. You’ll have to answer a wide range of questions that are specific to Lyft and require a high level of product management expertise.

Product sense questions alone account for over half (58%) of past candidates’ reported interview questions at Lyft, so you should be able to demonstrate that you can anticipate user problems and build products that solve them.

Thankfully, thorough preparation will boost your ability to answer these types of questions and land a job offer at Lyft. That’s why we’ve put together this ultimate guide to the Lyft PM interview: to maximize your chance of success.

Here's an overview of what we'll cover:

• Interview process and timeline
• Product sense interview questions
• Execution interview questions
• Leadership interview questions
• Preparation tips

Click here to practise 1-to-1 with PM ex-interviewers

1. interview process and timeline.

Similar to the timeline at Uber , the interview process for Lyft PMs typically takes around three to five weeks to complete.

Here’s a quick overview of the steps you’ll face along the way:

• Resume, cover letter, referrals
• Recruiter phone screen (30-45 min)
• First-round interviews (2 rounds, 45-60 min each)
• Onsite interviews (2-4 rounds, 45-60 min each)

Now let’s cover the above steps in more detail, so that you'll have a better idea of what to expect and what you'll need to prepare for.  For extra help, take a look at our list of  top 10 PM interview tips .

Note: if you are interviewing for a product leadership position (VP, Director, Group PM), learn more about the process and how to prepare here .

1.1 Resume, cover letter, referrals

First, recruiters will look at your resume and assess if your experience matches the open position. This is the most competitive step in the process, as millions of candidates do not make it past this stage.

You can use this free resume guide to help tailor your resume to the position you’re targeting. 

And if you’re looking for expert feedback, you can also get input from our team of ex-FAANG recruiters , who will cover what achievements to focus on (or ignore), how to fine tune your bullet points, and more.

1.2 Recruiter phone screen

After applying, the interview process typically kicks off with a call from an HR recruiter.

During this call, the recruiter will be digging into your background in order to confirm that you’ve got the necessary skills and qualifications for the role. Be ready to talk about your past experiences, especially those that you list on your resume, as well as why you’re a fit at Lyft.

The types of questions that you can expect will be typical behavioral and resume questions like “why Lyft?”, “ walk me through your resume ” and “tell me about a product that you’ve launched.”

If you need any clarification about the next steps in the process, this is a good time to ask. Your recruiter should be able to give you an overview of what to expect.

1.3 First-round interviews

Once you’ve passed the recruiter screen, there will be two PM-focused interviews. They may take place over video conference, on the phone, or in Lyft’s physical offices. They usually last for 45-60 minutes.

You’ll be interviewed by a Lyft PM, and you should be prepared for one product sense question and one execution question. You’ll have to dive deep into the problem, explain your reasoning, and work through your thoughts out loud. We’ll give you more details on product sense and execution in section 2.

If you crack the first interviews, your recruiter will move you on to the final round of onsite interviews. 

1.4 Onsite interviews

The last step in the process is the onsite portion, which consists of a loop of 2-4 separate interviews. This typically takes place in the Lyft offices, but may take place virtually depending on COVID-19 security measures.

Here, you can expect more product sense and execution interview rounds, as well as a leadership round, which will focus on behavioral and resume questions. We’ve also seen some reports of candidates being asked to give a presentation in one of their final rounds. This appears more frequently in senior PM roles.

As always, your recruiter should be able to provide more details on what you may need to prepare in advance for the onsite interviews.

If all goes well, the onsite interviews are your last step as a candidate, and from there you just have to wait to (hopefully) receive your offer. 

2. Question types

Now that you have an idea of the interview process at Lyft, let’s dive into the three types of questions that you can expect. Their interview rounds are very similar to Facebook’s PM interview process , with questions grouped into the following categories:

We've analyzed questions reported by former Lyft PM candidates on Glassdoor.com and categorized the real questions asked for each interview type, listed below. Note that some questions have been edited for clarity or grammar.

Let’s get started.

2.1 Product sense interview questions (58%)

Lyft PMs must be able to evaluate large, ambiguous problems and craft products that solve them. This is where you want to use your product design and product strategy skills.

During product sense interviews, interviewers are looking for candidates who are obsessed with the user, can clearly explain their logic behind each decision, and can break complex problems into manageable pieces.

Expect to play the role of a PM who is directing a team: deciding what to build and who should build it, determining a long-term vision, and anticipating setbacks. Explain your reasoning out loud so that your interviewer comes away with a clear understanding of your approach and working style.

Below, we’ve listed the real product sense questions that past candidates have reported on Glassdoor. These questions are a mix of product design , product improvement and product strategy questions . We recommend studying the articles we've written on each topic to learn how to answer these questions in a structured and impactful way.

Right, let’s get to some questions.

Example PM interview questions asked at Lyft: Product sense

Product design

• Design a dashboard for a food delivery service
• Design an advanced ticket purchase app for a commuter railroad
• Design the Caltrain mobile app
• How would you design the Lyft app for the blind?
• How would you design an efficient ETA system?
• Describe your process on developing an MVP for Lyft Kids.

Product improvement

• How would you improve Lyft?
• How would you improve the pin drop functionality for the Lyft app?
• How would you roll out an algorithm improvement for driver matching?
• How would you solve Lyft's commute problem?
• Tell me about a previous product you worked on and a feature you shipped
• How do we launch Lyft in a new city?
• If Lyft were to get into the parking business, what would you do?
• How could we get more drivers to come downtown during peak demand?

To look at the product sense interview in a bit more detail, check out our comprehensive guide .  This guide focuses on Facebook, but it could apply to any company. 

2.2 Execution interview questions (27%)

Once PMs have made a plan to tackle a problem, they must be able to execute on that plan. You’ll have to show that you can make key, data-based decisions based on analytical results.

This is the part of the interview to display that you have strong analytical and prioritization skills. Interviewers are looking for candidates who can get everything done in a logical order, evaluate trade-offs, and measure results using the most appropriate metrics.

Below, we’ve listed the real execution questions that past candidates have reported on Glassdoor. You’ll notice a fair amount of product metric questions in the mix. The article we’ve written on this topic can help you learn how to answer these questions in a measured, effective way.

Example PM interview questions asked at Lyft: Execution

• Measure the success of a new product and develop a dashboard for it
• What analytics should Lyft consider important?
• What are the KPI's that you would keep in mind for Lyft?
• Triage a drop in a metric by 5% WoW
• How would you execute and assure supply for surge pricing?
• There is a spike in cancellations this week. Why could this be the case?
• If a large number of drivers are dropping out of a particular city, why would it be?

To look at the execution interview in a bit more detail, check out our comprehensive guide .  This guide focuses on Facebook, but it could apply to any company. 

2.3 Leadership interview questions (15%)

PMs work with a range of different collaborators, such as engineers, designers, data analysts, etc. You’ll need to show that you’re capable of leading yourself and your team, in the face of diverse and unexpected challenges.

Interviewers will want to see that you can rally a cross-functional team across a variety of disciplines in order to collectively comprehend and tackle problems. You will have to demonstrate that you can adjust your leadership style to different personalities, make the most of your resources, and grow from past mistakes.

This interview will be the least structured of the three, but no less important than product sense and execution. Use relevant, concrete, and concise examples from your past to demonstrate the qualities that Lyft is looking for.

Below, we’ve listed the real leadership questions that past candidates have reported on Glassdoor. For more information, take a look at our behavioral interview guide , which is targeted at Facebook but contains a method that is applicable everywhere.

Example PM interview questions asked at Lyft: Leadership

• Why Lyft?   ( sample answer  from Amazon interviews)
• Walk me through your previous work
• Tell me about a challenge you faced
• Tell me about a situation when you disagreed with your boss
• How do you manage projects?
• How do you manage competing priorities?
• How do you handle ambiguity?

3. Preparation tips

Now that you know what questions to expect, let's focus on preparation. 

Below, you’ll find links to free resources and four introductory steps to help you prepare for your Lyft PM interviews.

3.1 Research the product / organization

As you may have noticed from the questions above, it is essential to inform yourself about the company and its products prior to the interviews.

If you neglect this step, you will likely struggle to answer Lyft’s product sense and execution questions, as well as the important “why Lyft?” question. In this case, interviewers may conclude that you don’t have enough of an interest in the company.

To study up on the company, you can start with videos like this one, which display some of Lyft's core values, such as Deliver Impact and Take Care of Each Other :

Here are some more resources to help you dive a bit deeper:

• Lyft’s mission statement and values (by Lyft)
• Lyft's product-focused Medium page (by Lyft engineering, via Medium)
• What to expect when interviewing at Lyft (by Dan Barak, ex-interviewer and lead product manager at Lyft)
• Lyft's business model (by Jungleworks, from 2016)

One really important thing to bear in mind is that, like most players in its industry, Lyft considers itself much more than simply a taxi app. With motorized scooters and bicycles a growing part of its service, and autonomous vehicles very much part of its long-term plans, Lyft considers itself to be part of the "MAAS" (mobility as a service) revolution.

Be ready to show you're aware of the key issues at play here; sustainability and environmental impact, safety, and changing regulatory frameworks are all factors that will affect you at product level, so be ready to talk intelligently about them.

3.2 Learn a consistent method for answering PM interview questions

As mentioned previously, Lyft will ask you questions that fall into certain categories like behavioral, design, strategy, estimation, and metric questions. Approaching each question with a predefined method will enable you to build strong interview habits.

Then, when it comes time for your interviews, these habits will reduce your stress and help you to make a great impression.

If you’re just looking for a jumping-off point, you can start learning about the different question types you’ll need to master in the following blog articles:

• Product design questions
• Product improvement questions
• Product strategy questions
• Product metric questions
• Leadership interview  ( Facebook guide that also applies to Lyft )
• Prioritization questions

Once you understand how to answer each question type, you also need to be able to communicate your answers clearly, under the pressure of interview conditions. That’s where practice comes into play.

3.3 Practice by yourself or with peers

In our experience, practicing by yourself is a great way to prepare for PM interviews. You can start practicing alone, asking and answering questions out loud, to help you get a feel for the different types of PM interview questions. It will help you perfect your step-by-step approach for each question type. And it also gives you time to correct your early mistakes.

You can find free practice questions on articles like this one or on YouTube.

If you have friends or peers who can do mock interviews with you, that's a great option too. This can be especially helpful if your friend has experience with PM interviews, or is at least familiar with the process.

3.4 Practice with experienced PM interviewers

Finally, you should also try to practice product manager mock interviews with expert ex-interviewers, as they’ll be able to give you much more accurate feedback than friends and peers. 

If you know a Product Manager who can help you, that's fantastic! But for most of us, it's tough to find the right connections to make this happen. And it might also be difficult to practice multiple hours with that person unless you know them really well.

That’s why we created a coaching service for candidates to practice 1-on-1 with ex-interviewers from leading tech companies. Learn more and start scheduling sessions today .

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Lyft Data Scientist Interview | Case Study

Lyft data scientist interview case study from a recent  instamentor  student.

Overall it took 5 weeks.

Candidate : N/A

How it gets started : Recruiter reached out on LinkedIn

Job level:  T5

Year of Experience : 5–10

Degree : M.S & B.S. in CS

Offer:  Yes

TC : ~450K USD

Location : San Francisco

Interview process : 5 weeks

Preparation:  2 months

Has a job:  yes

Decide to join:  N/A

Round 1: HR call

Why are you interested in Lyft, why do you wanna leave your current job, are you willing to relocate to San Francisco (in the city, where the HQ is based)

Round 2: Statistics & Probability & metrics

Fellow data scientist from the team gave a call and deep dive into the resume and focus on technical knowledge. 

How do you choose the right metrics to evaluate the healthy of Lyft's carpool service?

How do we know if we are performing well/poorly in this newly expanded city?

Round 3: Take-home data challenge

Given the existing A/B testing data, how can we improve the cancellation policy? What is your conclusion?

3 datasets: control + treatment 1 + treatment 2

Asked to submit a keynote presentation

Round 4: virtual onsite/final round

SQL: window functions, rank, lag/lead

Leadership/Behavioral questions. Tell me about a time you take a lead and go far and beyond for your customer. How do you influence others without being the manager?

Product case study: how to evaluate customer experience, what metrics to use, how to improve.

A/B testing. What if p-value is > 5%

Presentation. Based on the submitted homework, what is your conclusion, what should we do, anything actionable based on the data?

Final Offer

Total about 450k, 

~210k base salary

~220k from RSU (4-year vesting, total grant = 900k)

~25k sign-on bonus

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Ace Your Next Data Interview

Land a dream position at Amazon! Hi Leon, I hope you're doing well. I wanted to reach out and say thanks for your interview prep—it really helped me land a position at Amazon. It's been a fulfilling experience!

David, Data Engineer at Amazon