Bird Data Analyst Interview Questions + Guide in 2025

Bird is dedicated to making cities more livable and sustainable by providing affordable, eco-friendly transportation options, such as electric scooters, to reduce traffic and carbon emissions.

As a Data Analyst at Bird, you will be a crucial part of the data team, collaborating with cross-functional teams to drive data-driven decision-making and strategic initiatives. Your key responsibilities will include analyzing user interactions with Bird's marketplace, developing metrics to assess product health, and implementing experiments to optimize product offerings. Proficiency in SQL is essential, as you will be writing ETLs and conducting in-depth data analysis to derive actionable insights. Additionally, fluency in a programming language like Python or R will be beneficial for manipulating and visualizing data. The ideal candidate will possess strong analytical skills, a growth mindset, and excellent communication abilities to effectively present findings to both technical and non-technical stakeholders.

This guide aims to equip you with the knowledge and confidence to excel in your interview for the Data Analyst role at Bird by providing insights into the responsibilities and skills required for success in this position.

The interview process for a Data Analyst position at Bird is structured to assess both technical skills and cultural fit within the team. It typically consists of several rounds, each designed to evaluate different aspects of your capabilities and experiences.

1. Initial Phone Screen

The process begins with a phone screen, usually lasting about 30 minutes. This initial conversation is primarily with a recruiter and focuses on your background, interest in the role, and alignment with Bird's mission. Expect to discuss your previous experiences and how they relate to the responsibilities of a Data Analyst at Bird.

2. Technical Video Interview

Following the phone screen, candidates participate in a video interview with two team members. This round is less formal and does not heavily emphasize technical questions. Instead, it serves to gauge your skill set and preferred tools, as well as to understand how you might fit into the existing team dynamics.

3. Take-Home Assignment

Next, candidates are given a take-home assignment that typically involves SQL questions and a mini-project. This assignment is designed to assess your analytical capabilities and your ability to apply your skills to real-world scenarios. It may require you to analyze data and present your findings in a clear and actionable manner.

4. Onsite Interview

The final stage of the interview process is an onsite interview, often referred to as a "superday." During this round, candidates meet with multiple team members, including those from cross-functional teams. The onsite typically includes technical interviews focused on SQL, data analysis, and possibly some behavioral questions. Candidates should be prepared for SQL whiteboarding sessions and discussions about their approach to product-related questions. This round may also include a Q&A session with the hiring manager, allowing you to ask questions about the team and the company culture.

As you prepare for your interview, it's essential to be ready for a variety of questions that will test your technical knowledge and problem-solving skills.

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

Understand the Interview Process

The interview process at Bird typically begins with a phone screen focused on your background and interest in the role. This is followed by a video conversation with team members, where they will assess your skill set and tool preferences. Be prepared for a take-home assignment that may involve operational questions requiring strong analytical capabilities. The final stage usually consists of a superday with multiple technical interviews, including SQL whiteboarding sessions. Familiarize yourself with this structure to manage your time and energy effectively.

Master SQL and Analytical Skills

Given that SQL proficiency is crucial for this role, dedicate significant time to practicing SQL queries, especially focusing on groupby, aggregate functions, and complex joins. Utilize platforms like HackerRank and LeetCode to sharpen your skills. Additionally, brush up on your analytical skills, as you will need to distill large volumes of data into actionable insights. Be ready to demonstrate your ability to manipulate and visualize data using Python or R, particularly with libraries like Pandas.

Prepare for Behavioral Questions

Bird values a collaborative and inclusive culture, so expect behavioral questions that assess your fit within their team-oriented environment. Reflect on past experiences where you demonstrated teamwork, adaptability, and a growth mindset. Be ready to discuss how you handle challenges and how you can contribute to a positive team dynamic.

Communicate Effectively

Effective communication is key in this role, as you will need to present data-driven insights to cross-functional teams. Practice articulating your thought process clearly and concisely. Prepare to showcase your ability to create compelling dashboards and reports that make complex data easily understandable.

Embrace the Company Culture

Bird prides itself on being an ambitious and open-minded team. Familiarize yourself with their mission to make cities more livable and sustainable. Show your passion for their goals and how your skills align with their vision. Be prepared to discuss how you can contribute to their mission and how you embody their values of inclusion and collaboration.

Ask Insightful Questions

At the end of your interviews, you will likely have the opportunity to ask questions. Use this time to demonstrate your interest in the role and the company. Inquire about the data team's current projects, the tools they use, and how they measure success. This not only shows your enthusiasm but also helps you gauge if Bird is the right fit for you.

By following these tips and preparing thoroughly, you will position yourself as a strong candidate for the Data Analyst role at Bird. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Bird. The interview process will assess your technical skills, particularly in SQL and data analysis, as well as your ability to communicate insights effectively. Be prepared to demonstrate your analytical thinking, problem-solving abilities, and how you can leverage data to drive business decisions.

SQL and Data Manipulation

1. Can you explain the difference between INNER JOIN and LEFT JOIN in SQL?

Understanding SQL joins is crucial for data analysis, as they allow you to combine data from multiple tables.

How to Answer

Discuss the definitions of both joins and provide a scenario where each would be applicable. Highlight the importance of knowing how to retrieve the correct data based on the requirements.

Example

"An INNER JOIN returns only the rows where there is a match in both tables, while a LEFT JOIN returns all rows from the left table and the matched rows from the right table. For example, if I have a table of users and a table of orders, an INNER JOIN would show only users who have placed orders, whereas a LEFT JOIN would show all users, including those who haven't placed any orders."

2. How would you optimize a slow-running SQL query?

Performance optimization is key in data analysis to ensure timely insights.

How to Answer

Mention techniques such as indexing, avoiding SELECT *, and analyzing query execution plans. Provide a specific example if possible.

Example

"I would start by examining the execution plan to identify bottlenecks. If I notice that certain columns are frequently queried, I would consider adding indexes to those columns. Additionally, I would avoid using SELECT * and instead specify only the columns needed, which can significantly reduce the amount of data processed."

3. Describe a complex SQL query you wrote and the problem it solved.

This question assesses your practical experience with SQL.

How to Answer

Outline the problem, the approach you took, and the outcome. Be specific about the SQL functions and techniques you used.

Example

"I once wrote a complex query to analyze customer churn by joining multiple tables, including customer data, transaction history, and support tickets. I used window functions to calculate the churn rate over different periods, which helped the product team identify key factors contributing to customer retention."

4. What are aggregate functions in SQL, and can you provide examples?

Aggregate functions are fundamental for summarizing data.

How to Answer

Define aggregate functions and provide examples of common ones like COUNT, SUM, AVG, etc. Discuss their applications in data analysis.

Example

"Aggregate functions perform a calculation on a set of values and return a single value. For instance, I often use COUNT to determine the number of users in a specific segment, or AVG to calculate the average order value, which helps in understanding customer behavior."

5. How do you handle missing data in a dataset?

Handling missing data is crucial for accurate analysis.

How to Answer

Discuss various strategies such as imputation, removal, or using algorithms that support missing values. Provide a rationale for your chosen method.

Example

"I typically assess the extent of missing data first. If it's minimal, I might impute values based on the mean or median. However, if a significant portion is missing, I may choose to remove those records or use algorithms that can handle missing values, ensuring that the analysis remains robust."

Data Analysis and Visualization

1. How do you approach a new data analysis project?

This question evaluates your analytical process and project management skills.

How to Answer

Outline your steps from understanding the problem, gathering data, analyzing it, to presenting findings. Emphasize collaboration with stakeholders.

Example

"I start by clearly defining the problem and objectives with stakeholders. Then, I gather relevant data, ensuring its quality and completeness. After analyzing the data using statistical methods, I visualize the results using dashboards to communicate insights effectively to the team."

2. Can you describe a time when your analysis led to a significant business decision?

This question assesses your impact on the organization through data analysis.

How to Answer

Share a specific example where your analysis influenced a decision, detailing the process and outcome.

Example

"In a previous role, I analyzed user engagement metrics and discovered a significant drop-off at a specific point in the user journey. I presented my findings to the product team, which led to a redesign of that feature, resulting in a 20% increase in user retention."

3. What tools do you use for data visualization, and why?

Understanding visualization tools is essential for communicating data insights.

How to Answer

Mention specific tools you are proficient in and explain why you prefer them based on their features and usability.

Example

"I primarily use Tableau for data visualization due to its user-friendly interface and powerful capabilities for creating interactive dashboards. I also use Python libraries like Matplotlib and Seaborn for more customized visualizations when needed."

4. How do you ensure the accuracy of your data analysis?

Accuracy is critical in data analysis, and this question tests your attention to detail.

How to Answer

Discuss your methods for validating data and results, such as cross-referencing with other data sources or peer reviews.

Example

"I ensure accuracy by cross-referencing my findings with multiple data sources and conducting peer reviews of my analysis. Additionally, I perform sanity checks on the data to identify any anomalies before drawing conclusions."

5. What metrics do you consider most important for evaluating product success?

This question assesses your understanding of product metrics and their relevance.

How to Answer

Identify key metrics relevant to the role and explain why they matter for product evaluation.

Example

"I consider metrics like user engagement, retention rates, and customer satisfaction scores as critical indicators of product success. These metrics provide insights into how well the product meets user needs and its overall impact on the business."