Uber is a global leader in on-demand transportation, food delivery, and logistics. It has revolutionized the way people move by driving innovative solutions for efficient ride-sharing and transportation. The company employs over 5 million drivers who provide thousands of rides every hour, transforming the way people travel and interact worldwide.

To fuel this demand, Uber hires experienced software engineers, data engineers, data scientists, and data analysts to power an extensive logistics platform. Uber interview questions rigorously assesses candidates’ data expertise and creative problem-solving. In this guide, we’ll review each stage in the process and what areas to prepare for.

Uber is an international transportation network company offering peer-to-peer ridesharing, ride service hailing, food delivery, and a bicycle-sharing system

Uber’s interview process is tailored to evaluate a candidate’s technical aptitude, problem-solving abilities, and alignment with the company’s fast-paced culture. This includes the following stages:

**Preliminary Discussion:**A recruiter will reach out to learn more about a candidate’s background and interest in Uber. A more in-depth conversation with a hiring manager may follow to gauge specific skills and experiences.**Technical Interview:**This includes coding sessions and case studies to assess a candidate’s problem-solving abilities.**Functional Exercise:**A role-dependent assessment to gauge functional knowledge. Typically, these are case-study like exercises. For example, Uber might ask you what are the KPIs when launching the product in a new city.**Team Interview:**Here, interviews are conducted with potential team members and managers to evaluate the core skills needed for the position.

Uber’s interview process reflects its data-driven culture and emphasis on technical competency. Unlike other companies that may tailor their hiring process based on a pre-defined role, Uber tends to explore a candidate’s fit for the company through a variety of discussions and assessments. This approach ensures that the candidates are well-aligned with Uber’s dynamic and innovative work environment.

Having a deep understanding of databases and SQL is essential for all technical roles. Although Uber utilizes schema-less and document-storage engines, under the hood, they use MySQL together with the InnoDB storage engine.

Given the tables `users`

and `rides`

, write a query to report the distance traveled by each user in descending order. The `users`

table has columns `id`

and `name`

, and the `rides`

table has columns `id`

, `passenger_user_id`

, and `distance`

.

Given a table of `cars`

with columns `id`

and `make`

, write a query that outputs a random manufacturer’s name with an equal probability of selecting any name.

Given a `employees`

and `departments`

table, select the Top 3 departments with at least ten employees and rank them according to the percentage of their employees making over $100K in salary. The `employees`

table has columns `id`

, `first_name`

, `last_name`

, `salary`

, and `department_id`

. The `departments`

table has columns `id`

and `name`

.

*To further enhance your knowledge in Databases, explore the SQL learning path and practice with the SQL questions and solutions available in our database.*

Coding and algorithms are a major part of any technical role, especially at Uber. Here are some of the questions you might encounter during their technical interview:

You’re given a list of people to match together based on:

- A hard filter on scheduled availability
- A secondary filter based on similar interests

The goal is to optimize the total number of matches first, and then optimize on matches based on common interests.

Write a function to return a list of matches along their scheduled availability. If there’s an odd number or excess people that cannot be matched based on availability, return them in a separate list with their existing values.

You’re given a function that generates a floating-point number between 0 and 1 from a continuous uniform distribution.

Write a function `dice_rolls`

that uses this generator to simulate a dice roll, returning a number between 1 and 6 with a uniform distribution.

Given a list of `integers`

, and an integer `N`

, write a function `sum_to_n`

to find all combinations that sum to the value `N`

.

*To practice Coding and Algorithms interview questions, consider using the Python learning path or the full list of Coding and Algorithms questions in our database*.

Uber utilizes machine learning in multiple areas of their product, and it has become a core functionality of their services. Here are some machine learning questions typically asked at Uber:

Be sure to state your assumptions for each specific situation when answering this question. Does it change depending on the model? Are there alternative solutions?

Are all the assumptions weighted equally? Are there some that cannot be overcome in any situation?

What algorithm would you choose? What are the trade-offs between different classifiers? Discuss what features you would use in your model.

*To get ready for machine learning interview questions, we recommend taking the machine learning course.*

Analytics and experiments are crucial aspects of Uber’s continuous endeavor to optimize its services and understand user behavior. Through rigorous data analysis and well-structured experiments, Uber strives to make data-driven decisions to enhance user experience, optimize operational efficiency, and drive growth. Here are some typical questions you might encounter in this realm during your interview at Uber.

A car starts driving at 60 mph, and an hour later, another car leaves the same position going 80 mph. Calculate the time it will take for the second car to catch up with the first.

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 0.04 p-value.

Assess the validity of this result.

You work as a data scientist on a ride-sharing marketplace. Identify the metrics that would help you determine the demand for rides at any point. 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?

*For Analytics and Experiments, try using the product metrics and the data analytics learning paths. These resources will help you understand and solve complex problems in this field.*

Statistics and probability are the backbone of various analyses, experiments, and predictive models that drive decision-making at Uber. To prepare for these topics, try the following questions:

In your answer, discuss the relationship between hypothesis testing and p-values. Are there common misconceptions about what p-values represent?

Define Maximum Likelihood Estimation (MLE) and Maximum A Posteriori (MAP). When is it best to use each method?

A ride-sharing app has probability ** P** of dispensing a $5 coupon to a rider. The app services

If a driver using the app picks up two passengers, what’s the probability of both riders getting the coupon? What is the probability that only one of them will get the coupon?

*To master Statistics and Probability, try the Statistics and A/B testing and the Probability learning paths. These resources will provide you with a comprehensive understanding of the subject.*

Practice for the Uber interview with these recently asked interview questions.

Most data science positions fall under different position titles depending on the actual role.

From the graph we can see that on average the Product Manager role pays the most with a $165,530 base salary while the Business Analyst role on average pays the least with a $99,743 base salary.