Top 22 Uber Business Analyst Interview Questions + Guide in 2024

Considering Uber’s impressive earnings in 2023, we expect further business growth, presenting additional challenges for its business analysts to address. Uber business analysts are quick thinkers and pro communicators and solve complex product and operational challenges using business intelligence, metric development, and tools such as SQL, Excel, and Tableau.

Interview Query regularly analyzes interview experience data, which we’ve used to produce this guide. We’ve picked 22 popular Uber business analyst interview questions, provided an overview of the process, and our top tips and resources to help you prepare.

Business analysts at Uber analyze data to develop insights to drive business decisions for their products and operations.

The interview tests SQL, Excel, basic math, and data analytics proficiency, alongside communication and problem-solving skills through behavioral questions. SQL is an essential requirement, so practice concepts like window functions, subqueries, lead and lag functions, and complex joins. Basic statistical techniques like hypothesis testing, central limit theorem, and regression are also tested.

The Uber business analyst interview consists of the following steps:

Step 1: Preliminary Screening

After you apply, a recruiter will contact you to get a sense of your work experience and cultural fit. They may ask you why you want to join Uber and ask a couple of questions about your previous projects, so prepare appropriate responses.

Step 2: Online Test

For certain teams, you may be asked to take an online assessment on a platform like HackerEarth or CodeSignal that tests your SQL, Excel, and analytics skills. This will be a 90-minute test with around 28 questions on topics such as pivot tables, probability, standard deviation, and SQL joins. The questions are easy, but you’ll need to be quick.

Step 3: Technical Interview

The next step is a technical interview with a senior business analyst. They will ask you questions about SQL, Python, and Excel, your past projects, and high-level business case studies to examine your analytical thinking.

Step 4: Case Interviews/Panel Discussion

You will then be invited to interview with analytics managers on-site. This step will consist of four rounds. One will be a panel interview, during which you will present your findings from a dataset provided before the interviews. The other three will be 30-minute rounds focusing on your business acumen via case studies and SQL questions.

Here are some interview tips based on Uber’s Careers page:

1. Communication is key—if you don’t understand a question, ask for clarification.
2. Solve out loud—they’ll want to know how you engage with a problem as much as your solution.
3. Show initiative.
4. Display good time-management skills.

Let’s now dive into the top questions asked by Uber in their analyst interviews. Try to solve the questions independently before looking at the solutions. Remember that the interviewer will gauge how well you handle open-ended questions and how creative and articulate you are at thinking through problems while solving them.

It’s helpful to engage with Uber’s products like Rides and Eats from the mindset of someone who is tasked with improving them. For behavioral questions, follow the STAR framework and research Uber, its cultural values, and its commitment to diversity, equity, and inclusion.

1. Walk me through your resume.

Your response will help your interviewer gauge how well you can present and tell a compelling story about yourself. It will also give them an overview of your key achievements.

How to Answer

Talk about your previous roles and projects in a way that relates to the position at hand, particularly those involving data-driven problem-solving and cross-functional collaboration. Be concise, and don’t forget to highlight outcomes.

Resource: Explore our detailed guide on the behavioral questions that analysts are often asked, which includes a tried-and-tested framework to solve them.

Example

“I hold a bachelor’s degree in information systems, which laid the foundation for my skills in data analysis and business process modeling. My first role was as a junior analyst at [Company A], where I helped maintain performance dashboards to support data-driven decision-making. After two years there, I moved to [Company B], where I worked as a business analyst, leading projects involving data integration for business intelligence solutions. I’m particularly proud of one project where our team optimized our data collection process and reduced errors by 30%. As a result, we were able to save around thirty work hours per week.”

2. Why do you want to join Uber?

Interviewers will want to know why you chose the analyst role at Uber and if you’re passionate about the company’s culture and values.

How to Answer

Your answer should reflect your understanding of Uber’s work, culture, and the specific opportunities that attract you to the company. Be honest and specific about how Uber’s offerings align with your career goals.

Example

“Working at Uber would give me a chance to be on a team that values innovation, promotes learning, and impacts millions of lives daily. I’m intrigued by Uber’s innovative approach to solving real-world transportation challenges, its global impact, and the opportunity to work with diverse teams.”

3. How have you used data to inform a decision?

This question tests whether you have practical experience using analytics to influence business outcomes, as this is the crux of the business analyst role.

How to Answer

Describe a relevant scenario following the STAR framework. Make your answer as business-focused as possible, where data is simply a tool you use to drive a business decision. If it was a team effort, specify your role in the process.

Example

“In my previous company, our product manager asked us to see if expanding a particular product line would be profitable. I conducted an ad-hoc analysis to explore customer purchase data and market trends to identify high-demand products. I used SQL for data querying and Tableau for visualization to present my findings. My analysis suggested a significant market opportunity for eco-friendly products, which were trending positively among our core demographic. Based on my recommendation, the company launched a new line of eco-friendly products, which resulted in a 20% boost in sales within the first six months.”

4. Tell me about a conflict you’ve had with a co-worker.

This question checks your emotional intelligence and conflict resolution skills—both critical to being a good team player at Uber.

How to Answer

Describe a conflict in which you played a role in finding a mutually beneficial outcome. Highlight what you learned from the experience, showing you are flexible and have a growth mindset.

Example

“I once had a conflict with a co-worker over prioritizing project features. To resolve it, I set up a one-on-one to discuss our viewpoints and come to an agreement. We decided to consult other team members and gather more user data to make an informed decision. This experience helped me appreciate the importance of empathy and flexibility in teamwork.”

5. Describe a time when you explained a complex technical problem to someone from a non-technical background.

Uber analysts work closely with technical and non-technical team members. Expect data communication questions that test your ability to convey complex technical information.

How to Answer

Focus on an instance where you broke down a technical issue for a non-technical audience. Use the STAR method of storytelling. Discuss the Specific situation you were challenged with, the Task you decided on, the Action you took, and the Result of your efforts.

Example

“In my previous role, I was once tasked with explaining a complex cloud integration issue to a client unfamiliar with cloud computing. I compared the process to merging different departments within a company, each with its unique processes and data. I used minimal technical jargon. This helped the client grasp the problem’s challenges.”

6. Given a table of account statuses, write a query to get the percentage of accounts that were active on December 31, 2019, and closed on January 1, 2020, over the total number of accounts that were active on December 31. Assume that each account has only one daily record indicating its status at the end of the day.

This is a typical data extraction job you can expect at Uber for purposes like analyzing user churn.

How to Answer

Explain your approach to structuring an optimized SQL query and mention which functions you would use.

Example

“I’d first create a subset of data by identifying all accounts that were active on December 31, 2019. Then I’d filter out accounts from this subset that were closed on January 1, 2020, before calculating the percentage. I’d use the COUNT() function on both subsets to count the relevant accounts and then divide the count of accounts closed on January 1st by the count of active accounts on December 31. The key is to ensure that data is accurately filtered by date and status in each step.”

7. Discuss how you would visualize the variation in Uber ride prices throughout the day across different cities.

This evaluates your ability to present complex data in an accessible way while understanding the nuances of the chosen BI tool.

How to Answer

Discuss relevant KPIs and how you would choose them. Explain how you would structure the dashboard for clarity and ease of use and how you would tailor your dashboard or build layers depending on the end user.

Example

“Choosing KPIs that align with business objectives is crucial; for example, focusing on times and areas with the highest price fluctuations can offer insights into demand patterns. So, I’d track KPIs such as average price, peak price times, and ride demand. I’d customize views according to the end-users; operational teams might need detailed hourly data, while executives usually prefer a daily summary highlighting trends and anomalies.”

8. Given an employees and departments table, select the top 3 departments with at least 10 employees and rank them according to the percentage of their employees making over $100,000.

This SQL question reflects real-world scenarios at Uber where studying and segmenting departmental performance based on specific criteria is needed for resource allocation.

How to Answer

Outline the steps you’ll take to answer the question. Explain how you would join any necessary tables, use aggregation functions to calculate totals or averages, and apply conditions to filter the results.

Example

“I would join employees and departments tables on the appropriate key. Then, I’d group the results by department and use conditional aggregation to find the number of employees making over $100,000 in each department. I would use the HAVING clause to implement the filtration criteria.”

9. What is the difference between COUNT, COUNTA, COUNTBLANK, and COUNTIF functions?

This question tests your proficiency with Excel, a crucial tool for exploring data for ad hoc analyses.

How to Answer

Focus your response on how each helps in different types of scenarios. Provide examples.

Example

“COUNT is used to tally the number of cells that contain numbers in a range. COUNTA counts all cells in a range that are not empty. COUNTBLANK is used to identify empty cells, for example, to get the number of null values in a dataset. COUNTIF provides a count of cells that meet a specific condition, such as counting the number of trips that exceeded a certain fare amount.”

10. A multinational retail corporation stores sales data from branches worldwide in separate tables according to the year the sales were made. The current data structure is proving inefficient for business analytics. Write a query to create a pivot table that shows total sales for each branch by year.

As a business analyst, you’ll be tasked with streamlining various processes for efficiency and ease of doing business.

How to Answer

Outline the process of creating a pivot table using SQL or Excel, emphasizing the steps to aggregate data by branch and year.

Example

“First, I would combine the sales data from the various tables into a single table using a UNION ALL, ensuring each record is tagged with the correct branch and year. Then, I’d create a pivot table that groups this combined data by branch, with columns for each year to show total sales. This approach helps in quickly identifying sales trends over the years for each branch.”

11. How do you measure the success of a product?

Questions may be deliberately ambiguous, as Uber wants you to be adept at handling open-ended problems.

How to Answer

Discuss the selection of specific KPIs based on the product objectives and the industry context. Mention the importance of both quantitative and qualitative metrics to gain a comprehensive view of success.

Example

“We should first define what success looks like in the context of the product’s goals—whether it’s market penetration, profitability, user growth, or customer satisfaction. If Uber is evaluating a new ride-sharing feature, we might look at user adoption rates, revenue generated versus forecasted, and customer feedback through ratings and reviews. This holistic approach ensures we capture financial and operational performance and understand how users receive the product.”

12. Let’s say you are managing products for an e-commerce store. You think products from a particular category have a lower average price than those in all other categories. Calculate the t-value and degrees of freedom for such a test.

Skills like hypothesis testing and basic statistical analysis are needed as analysts have to statistically validate assumptions about data to make informed decisions.

How to Answer

Explain the method for calculating the t-value. Discuss the steps to determine sample means, variance, and sample sizes for both groups. Mention the assumptions you’d make, like normality and equal variance.

Example

“I’d first calculate the mean prices for both the category in question and all other categories. Then, I would use the formula for the t-test statistic, which compares the difference between the two means relative to the variability of the prices, scaled by the sample size. The degrees of freedom for this test would be the sum of the two sample sizes minus two. This allows us to understand if the observed difference in means is statistically significant or due to random chance.”

13. We’d like to understand if a new driver incentive program is increasing the number of trips drivers accept. What statistical methods would you use to evaluate its effectiveness?

This question checks your understanding of using statistical methods to measure the impact of Uber’s new initiatives.

How to Answer

Highlight a combination of methods for a well-rounded analysis. Briefly explain how each helps evaluate the program’s influence.

Example

“I’d propose an A/B testing framework, where drivers are randomly assigned to either receive the new incentives or continue with the existing conditions. This method allows us to control for external variables that could influence the results. I would then analyze the data using statistical tests, such as the t-test, to compare the average number of trips accepted between the two groups, ensuring any observed differences are statistically significant. Additionally, I’d consider employing regression analysis if there’s a need to adjust for confounding variables.”

14. Write a query to get the total three-day rolling average for deposits by day.

Similar analyses might be applied to daily ride bookings, driver earnings, or customer deposits for Uber to manage resources efficiently.

How to Answer

Mention the rolling average formula and the SQL clauses you’d use before you explain your solution.

Example

“The rolling average is the sum of a set of values divided by the number of values. In this case, the set consists of the deposit amounts for three consecutive days.

I would write a query to select the date and deposit amounts from the deposits data table. Next, using the AVG() function within a window defined by the OVER() clause, I would specify the window to consider the current row and the two preceding rows. This is done by setting ROWS BETWEEN 2 PRECEDING AND CURRENT ROW in the OVER() clause.”

15. Uber is testing a new feature that recommends the most efficient routes to drivers in real time. There’s a 70% chance that a recommended route is the fastest. If a driver follows three recommended routes in a day, what is the probability that at least two of the three routes are indeed the fastest?

Mathematical skills, especially probability and statistics, are necessary to handle Uber’s operational challenges, especially in problems related to prediction and pricing.

How to Answer

Break down the problem and explain the concept of binomial probability clearly.

Example

“To solve this problem, I’d use the binomial probability formula, as the scenario involves multiple independent events with a fixed probability of success. I would calculate the probability of the driver following exactly two or three recommended routes and sum them to find the overall probability of the driver following at least two fastest routes.”

16. Let’s say you’re given 90 days of ride data. How would you use it to project the lifetime value of a new driver on the system?

Success metrics like driver lifetime value are essential in Uber’s business planning and strategy. This question tests your product sense and your ability to forecast long-term metrics.

How to Answer

Discuss how you would use historical data to calculate average earnings over a period, factor in driver churn rates, and apply a predictive model to estimate future earnings and engagement.

Example

“First, I’d analyze the data to calculate average earnings per driver and retention rates. Then, considering seasonal variations and growth in ride demand, I’d use these insights to project average monthly earnings. By combining these insights with historical churn rates, I’d model the expected active months for a new driver. Multiplying the projected monthly earnings by the expected active months would give us an estimate of the lifetime value of a new driver.”

17. What should be the main success metric for Uber Pool?

This gauges your business acumen and product sense, which are needed skills for analysts to help Uber achieve its business objectives.

How to Answer

A great way to approach these is to consider the following:

• What are the company goals concerning this product?
• What problem does this product solve?

Then, follow the framework of asking clarifying questions and stating your assumptions before diving into the solution.

Resource: This guide delves into the framework of a good case study solution and includes practice problems.

Example

“The main success metric for Uber Pool should be the average occupancy rate per trip. This metric indicates how well the service maximizes the number of passengers per vehicle, which directly impacts cost efficiency and sustainability. By monitoring this rate, Uber can also assess the effectiveness of its matching algorithms. An increasing occupancy rate suggests more successful pooling, which helps reduce costs per ride, cuts down on emissions, and can potentially lower prices for users.”

18. Given a list of timestamps in sequential order, return a list of lists grouped by week (7 days) using the first timestamp as the starting point.

This question tests your handling of time-series data in Python. Uber might need this to analyze weekly trends in ride requests or driver activity.

How to Answer

While giving your solution, mention which Python functions and libraries you would use. Highlight potential edge cases like missing or duplicate timestamps and briefly touch on the importance of preprocessing steps.

Example

“I would first ensure that all timestamps are in the correct datetime format and are sorted in ascending order. This is crucial because any misalignment in sequence can skew the week grouping. I’d also check for any missing timestamps or outliers that could disrupt the weekly intervals. Using the first timestamp as the base, I’d subtract this base timestamp from the rest to get a timedelta object for each timestamp. Then, I’d convert these timedelta values into days and divide by 7 to determine the week number relative to the first timestamp. Each week can then be grouped using the groupby() function in pandas.”

19. Ride cancellations have shot up 4.5% week-over-week. How would you investigate what’s going on?

This is an example of common ad hoc analyses you’d be expected to conduct as an Uber business analyst. Remember: your approach should be efficient as stakeholders often expect a quick turnaround for such problem statements.

How to Answer

Outline a structured approach to investigate the issue, starting with data verification and followed by deeper analysis to identify potential causes. Mention the value of data visualization, segmentation, and hypothesis testing.

Example

“I’d verify the data first to rule out any reporting or input errors. Then, I’d use visualization tools to examine trends in cancellation rates across different regions and times. I would segment the data by various dimensions, such as rider demographics, driver ratings, geographical areas, time of day, and specific days of the week to identify anomalies. Additionally, I’d review any recent changes in Uber’s policies, app updates, or external factors like weather conditions or local events that could influence rider behavior.”

20. What metrics would you look at to determine ride demand? How can you determine the threshold for too much demand?

Understanding and predicting ride demand is central to Uber’s operations, as it impacts everything from pricing strategies to driver distribution.

How to Answer

Focus on metrics reflecting riders’ requests and driver availability. Highlight how looking at these metrics across certain times and regions helps identify areas with potential strain.

Example

“To determine the demand for rides at any point, I would look at ride requests, completed rides, average wait time, and surge pricing. I would examine ride requests exceeding supply, increased wait time, and surge pricing. Finally, I would consider driver utilization rate, surge pricing multiplier, and customer feedback to determine the threshold for too much demand.”

21. Let’s say we want to build a model to predict the time spent for a restaurant to prepare food from the moment an order comes in until the order is ready. What kind of model would we build and what features would we use?

This question evaluates your understanding of model selection and feature engineering, which are crucial skills for building predictive models in a business context.

How to Answer

Focus on features that capture the complexity of the order, the operational load in the kitchen, and the context of the order time. Highlight how these features, when analyzed together, can provide a reliable prediction of preparation time.

Example

“To predict the time spent preparing an order, a multiple linear regression model would be effective. This model could incorporate features such as the number of dishes in the order, the number of modifications, and the time of day. For instance, during peak hours like lunch, preparation times might increase due to higher order volumes. Additionally, staffing levels could also influence preparation times, with more cooks reducing the time needed. By including these variables, the model could provide a more accurate prediction of preparation time, with a 95% confidence interval to account for variability.”

22. What are the assumptions of linear regression?

This question assesses your understanding of the foundational assumptions necessary for applying linear regression models effectively.

How to Approach

Identify and explain the key assumptions of linear regression, emphasizing why each one is critical to the model’s accuracy and reliability.

Example

“The first assumption in linear regression is that there is a linear relationship between the predictor variables and the response variable. For instance, if we’re predicting house prices, the model assumes that an increase in size or proximity to downtown will linearly affect the price. Next, the assumption of additivity suggests that the effect of one predictor on the response is independent of other predictors. If the impact of size on price only increases when a house is downtown, it would violate this assumption. Furthermore, the assumption of no multicollinearity ensures that predictor variables are not highly correlated, as this could distort the model’s estimations. Finally, the errors in the model should be independently, identically, and normally distributed, which ensures that the predictions are unbiased and that the variance in the errors is constant across all levels of the predictor variables.”

Here are some tips to help you excel in your interview:

Study the Company and Role

Research Uber’s recent news and updates, values, and business challenges. Understanding the company’s culture and strategic goals will help you present yourself well and assess if they are a good fit for you.

Then, once you understand the company’s position, seek to understand how the specific team you are applying for supports the company’s goals.

Read Uber’s article on their hiring process to learn more.

Brush Up on Technical Skills

Be proficient in statistics, product sense, Excel, and metric development. Practice SQL problems that include window functions, complex joins, subqueries, lead and lag functions, etc.

Check out our free resources for analysts, such as our collections of business analyst SQL interview questions, top Uber interview questions, Excel questions for analysts, and business analyst interview questions.

A great way to boost your confidence is to work on projects that mimic real-world analytics challenges. Check our article on our handpicked data analytics projects.

Prepare Behavioral Interview Answers

Soft skills like collaboration, effective communication, and flexibility are paramount to succeeding in any job, especially in the collaborative culture at Uber.

Try a mock interview to test your current preparedness for the interview process and to improve your communication skills.

Ask the Interviewer Well-Thought-Out Questions

Have relevant questions ready for your interviewer. This will demonstrate your interest in the Uber role and give you valuable insights into what it’s like to work there.

If you need additional guidance, we also offer tailored product metrics, SQL, and data analysis learning paths covering core topics and practical applications.

What is the average salary for a business analyst role at Uber?

The average base salary for a business analyst at Uber is $99,743, making the remuneration considerably higher than the average base salary for general BA jobs in the US at $80,835.

What other companies can I apply to besides Uber’s business analyst role?

You can apply for roles in MAANG companies or similar ride-sharing companies like Lyft. We have interview guides for Google, Apple, Amazon, Meta, Netflix, and Lyft.

You can read about other firms’ interview processes on our Company Interview Guides page.

Are there job postings for Uber business analyst roles on Interview Query?

We don’t have any BA openings at Uber listed on our job portal right now, although we expect positions to open up later. You can have a look at similar roles, filtering by location, firm, and seniority level on the portal.

Succeeding in Uber business analyst interview questions requires a strong understanding of their products and business, fundamental statistical knowledge, and the ability to creatively apply your technical skills to solve their business challenges.

Understanding Uber’s experimentation-driven culture and preparing thoroughly with both technical and behavioral questions will be key to succeeding.

For other data-related roles at Uber, consider exploring our guides for data engineer, software engineer, machine learning engineer, and data analyst positions in our main Uber interview guide.

Best wishes on your journey to securing a fulfilling role at Uber!