Better Data Analyst Interview Questions + Guide in 2025

Better is a technology-driven homeownership company focused on transforming the mortgage industry by making home finance faster, cheaper, and more accessible for everyone.

The Data Analyst role at Better is integral to the Growth team, tasked with enhancing the company's direct-to-consumer revenue strategies through data-driven insights. Key responsibilities include applying quantitative analysis to understand user interactions with marketing and product, optimizing paid media campaigns based on market trends, and collaborating with cross-functional teams to improve acquisition and engagement strategies. A strong understanding of SQL, statistics, and analytics is essential, along with the ability to conduct hypothesis testing and creative analysis. Candidates should demonstrate a growth mindset, a keen attention to detail, and the capability to balance strategic thinking with execution. Previous experience in a startup environment and familiarity with marketing tools and programming languages will be advantageous.

This guide will equip you with the knowledge and skills necessary to excel in your interview, enhancing your ability to articulate your fit for the Data Analyst role at Better.

The interview process for a Data Analyst at Better is structured to assess both technical skills and cultural fit within the organization. It typically consists of several rounds, each designed to evaluate different competencies relevant to the role.

1. Initial Screening

The first step in the interview process is an initial screening, usually conducted by a recruiter. This 30-minute phone call focuses on understanding your background, skills, and motivations for applying to Better. The recruiter will also provide insights into the company culture and the specifics of the Data Analyst role, ensuring that you have a clear understanding of what to expect.

2. Technical Interview

Following the initial screening, candidates will participate in a technical interview. This round is typically conducted via video call and lasts about 45 minutes. During this interview, you will be assessed on your proficiency in SQL, particularly your understanding of window functions and logical reasoning. Expect to tackle practical problems that require you to demonstrate your analytical skills and ability to interpret data effectively.

3. Team Interviews

The next phase involves interviews with team members, including a team lead and a manager. These interviews are designed to evaluate your collaborative skills and how well you can work within a team environment. You may be asked to discuss past projects, your approach to data analysis, and how you handle challenges in a team setting. This is also an opportunity for you to showcase your understanding of marketing channels and how data influences decision-making.

4. Final Interview with HR

The final step in the interview process is a conversation with an HR representative. This interview focuses on cultural fit and your long-term career aspirations. HR will assess your alignment with Better's values and mission, as well as discuss compensation and benefits. This is also a chance for you to ask any remaining questions about the company and the role.

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

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

Master SQL and Analytical Skills

Given the emphasis on SQL and analytical skills in the role, ensure you are well-versed in SQL queries, particularly window functions, complex joins, and data manipulation techniques. Prepare to demonstrate your analytical thinking by discussing how you have used data to drive decisions in previous roles. Practice solving SQL problems and be ready to explain your thought process clearly.

Prepare for Guesstimates

Expect to encounter guesstimate questions during your interview. These questions assess your logical reasoning and problem-solving abilities. Practice common guesstimate scenarios, such as estimating market sizes or conversion rates, and be prepared to walk through your reasoning step-by-step. This will showcase your analytical mindset and ability to think on your feet.

Understand the Company’s Growth Strategy

Familiarize yourself with Better's mission to transform home finance and its innovative approach to the mortgage industry. Be prepared to discuss how your skills and experiences align with their growth strategy. Consider how you can contribute to optimizing marketing activities and improving user engagement through data-driven insights.

Emphasize a Growth Mindset

Better values individuals who are eager to learn and grow. Highlight your willingness to take on new challenges and your experience in adapting to fast-paced environments. Share examples of how you have embraced feedback and used it to improve your performance, as this aligns with the company’s culture of continuous improvement.

Showcase Cross-Functional Collaboration

The role requires working closely with various teams, including Creative, Marketing, and Product. Prepare to discuss your experience in cross-functional collaboration and how you have successfully partnered with different departments to achieve common goals. Highlight any specific projects where your analytical insights led to improved outcomes.

Be Ready for Behavioral Questions

Expect behavioral questions that assess your fit within Better's culture. Prepare examples that demonstrate your problem-solving skills, attention to detail, and ability to balance strategic thinking with execution. Use the STAR (Situation, Task, Action, Result) method to structure your responses effectively.

Display Enthusiasm for the Mission

Show genuine enthusiasm for Better's mission to make homeownership more accessible. Research recent developments in the fintech space and be ready to discuss how you can contribute to the company's goals. Your passion for the industry will resonate with interviewers and demonstrate your alignment with the company’s values.

By following these tips, you will be well-prepared to showcase your skills and fit for the Data Analyst role at Better. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Better. The interview process will likely focus on your analytical skills, particularly in SQL, statistics, and your ability to interpret data to drive business decisions. Be prepared to demonstrate your understanding of marketing analytics, performance management, and your experience with data visualization tools.

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 manipulation and analysis.

How to Answer

Explain the basic definitions of both INNER JOIN and LEFT JOIN, and provide a scenario where each would be used.

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 customers and a table of orders, an INNER JOIN would show only customers who have placed orders, whereas a LEFT JOIN would show all customers, including those who haven’t placed any orders.”

2. What are window functions in SQL, and can you provide an example of how you would use one?

Window functions are essential for performing calculations across a set of table rows related to the current row.

How to Answer

Define window functions and describe their purpose, then provide a specific example of a use case.

Example

“Window functions allow you to perform calculations across a set of rows that are related to the current row. For instance, I might use the ROW_NUMBER() function to assign a unique sequential integer to rows within a partition of a result set, which can be useful for ranking customers based on their total purchases.”

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

Performance optimization is key in data analysis roles.

How to Answer

Discuss various strategies for optimizing SQL queries, such as indexing, query restructuring, and analyzing execution plans.

Example

“To optimize a slow-running SQL query, I would first analyze the execution plan to identify bottlenecks. I might add indexes to columns that are frequently used in WHERE clauses or JOIN conditions. Additionally, I would look for opportunities to simplify the query by removing unnecessary subqueries or using more efficient JOIN types.”

4. Describe a complex SQL query you have written. What was its purpose?

This question assesses your practical experience with SQL.

How to Answer

Provide a brief overview of the query, its purpose, and the outcome it achieved.

Example

“I wrote a complex SQL query to analyze customer purchase behavior over time. The query involved multiple JOINs across several tables, aggregating data to show total purchases by month and segmenting by customer demographics. This analysis helped the marketing team tailor their campaigns to specific customer segments.”

Statistics and Probability

1. What is the Central Limit Theorem, and why is it important?

Understanding statistical concepts is vital for data analysis.

How to Answer

Define the Central Limit Theorem and explain its significance in statistics.

Example

“The Central Limit Theorem states that the distribution of the sample means approaches a normal distribution as the sample size increases, regardless of the population's distribution. This is important because it allows us to make inferences about population parameters even when the population distribution is unknown, as long as we have a sufficiently large sample size.”

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

Handling missing data is a common challenge in data analysis.

How to Answer

Discuss various methods for dealing with missing data, such as imputation, deletion, or using algorithms that support missing values.

Example

“I handle missing data by first assessing the extent and pattern of the missingness. Depending on the situation, I might use imputation techniques, such as filling in missing values with the mean or median, or I might choose to delete rows with missing values if they are not significant. In some cases, I may also use algorithms that can handle missing data without requiring imputation.”

3. Can you explain the difference between Type I and Type II errors?

Understanding hypothesis testing is crucial for data-driven decision-making.

How to Answer

Define both types of errors and provide examples of each.

Example

“A Type I error occurs when we reject a true null hypothesis, essentially a false positive. For example, concluding that a new marketing strategy is effective when it is not. A Type II error occurs when we fail to reject a false null hypothesis, or a false negative, such as concluding that a strategy is ineffective when it actually is effective.”

4. What is A/B testing, and how would you implement it?

A/B testing is a common method for evaluating marketing strategies.

How to Answer

Explain the concept of A/B testing and outline the steps you would take to implement it.

Example

“A/B testing involves comparing two versions of a variable to determine which one performs better. To implement it, I would first define the goal of the test, create two versions of the variable, randomly assign users to each version, and then analyze the results using statistical methods to determine if there is a significant difference in performance.”

Analytics and Business Insights

1. How do you prioritize which metrics to track for a marketing campaign?

This question assesses your analytical thinking and business acumen.

How to Answer

Discuss the importance of aligning metrics with business goals and the specific metrics you would consider.

Example

“I prioritize metrics based on their alignment with the campaign’s objectives. For instance, if the goal is to increase brand awareness, I would focus on metrics like reach and impressions. If the goal is to drive conversions, I would track metrics such as click-through rates and conversion rates. I also consider the customer journey and how each metric impacts overall business performance.”

2. Describe a time when your analysis directly influenced a business decision.

This question evaluates your impact as a data analyst.

How to Answer

Provide a specific example of your analysis and the resulting business decision.

Example

“In my previous role, I conducted an analysis of customer churn rates and identified that a significant number of customers were leaving after their first purchase. I presented my findings to the marketing team, which led to the implementation of a targeted follow-up campaign for first-time buyers. This initiative resulted in a 20% increase in repeat purchases over the next quarter.”

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

Data visualization is key for presenting insights effectively.

How to Answer

Discuss the tools you are familiar with and their advantages.

Example

“I primarily use Tableau and Google Data Studio for data visualization. Tableau allows for complex visualizations and is great for interactive dashboards, while Google Data Studio is user-friendly and integrates well with other Google products. Both tools help me present data in a way that is easily understandable for stakeholders.”

4. How do you ensure data quality in your analyses?

Data quality is critical for accurate insights.

How to Answer

Discuss the steps you take to validate and clean data before analysis.

Example

“To ensure data quality, I start by performing data validation checks to identify any inconsistencies or anomalies. I also implement data cleaning processes, such as removing duplicates and correcting errors. Additionally, I document my data sources and methodologies to maintain transparency and reproducibility in my analyses.”