Freewheel Business Intelligence Interview Questions + Guide in 2025

Freewheel is a technology company that specializes in the intersection of media and advertising, offering innovative solutions to optimize ad delivery and maximize revenue for its clients.

The Business Intelligence role at Freewheel is pivotal in transforming data into actionable insights that drive strategic decisions. Key responsibilities include analyzing large datasets, developing reporting tools, and collaborating with cross-functional teams to inform product development and marketing strategies. A successful candidate will have strong analytical skills, proficiency in data visualization tools, and an understanding of advertising metrics. Experience with SQL and data modeling is essential, while familiarity with the media landscape is a plus. Traits such as attention to detail, problem-solving capabilities, and the ability to communicate complex data insights clearly will be crucial for success in this role.

This guide will help you prepare by providing context about the expectations and skills needed for the Business Intelligence position at Freewheel, enabling you to approach your interview with confidence and clarity.

The interview process for a Business Intelligence role at Freewheel is structured to assess both technical skills and cultural fit within the organization. It typically consists of several stages, each designed to evaluate different aspects of a candidate's qualifications and experience.

1. Initial Screening

The process begins with an initial phone screening, usually conducted by an HR representative. This conversation is generally brief and focuses on your background, experience, and motivation for applying to Freewheel. Expect to discuss your previous projects and how they relate to the role you are applying for. This is also an opportunity for you to ask questions about the company culture and the specifics of the Business Intelligence team.

2. Technical Assessment

Following the initial screening, candidates often complete a technical assessment, which may take the form of an online coding challenge. This assessment typically includes a set of programming problems that test your analytical and problem-solving skills, often focusing on algorithms and data structures. Candidates should be prepared for questions that may involve SQL and data manipulation, as these are crucial skills for a Business Intelligence role.

3. Phone Interviews

After successfully completing the technical assessment, candidates usually participate in one or more phone interviews. These interviews may be conducted by the hiring manager or team members and often delve deeper into your technical expertise, including your experience with data analysis tools and methodologies. Expect to discuss specific projects you've worked on, as well as your approach to problem-solving in a business context.

4. Onsite Interview

The onsite interview is a more comprehensive evaluation, typically lasting several hours and involving multiple interviewers. Candidates may be asked to present a case study or a project they have worked on, demonstrating their analytical skills and ability to communicate complex information effectively. This portion of the interview often includes both technical questions and behavioral assessments to gauge how well you would fit within the team and the company culture.

5. Final Interview

In some cases, a final interview may be conducted with senior management or executives. This interview focuses on your long-term career goals, your vision for the role, and how you can contribute to the company's objectives. It is also an opportunity for you to ask high-level questions about the company's direction and strategy.

As you prepare for your interview, consider the types of questions that may arise in each of these stages, particularly those that relate to your technical skills and past experiences.

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

Understand the Company’s Current Landscape

Given the recent structural changes at Freewheel, it’s crucial to familiarize yourself with the company’s current direction and challenges. Research any recent news articles, press releases, or updates that may provide insight into how these changes could impact the Business Intelligence team. This knowledge will not only help you answer questions more effectively but also demonstrate your genuine interest in the company.

Prepare for a Variety of Interview Formats

The interview process at Freewheel can include multiple formats, such as phone screens, coding challenges, and presentations. Be ready for a mix of technical and behavioral questions. For instance, you might be asked to discuss past projects or present a technical topic. Practicing your presentation skills and being able to articulate your experiences clearly will be beneficial.

Brush Up on Technical Skills

Expect to encounter technical questions that assess your proficiency in SQL, Python, and data analysis concepts. Review common data structures and algorithms, as well as dynamic programming problems, as these have been noted in previous interviews. Additionally, be prepared to discuss your experience with big data technologies, as this knowledge is often relevant for Business Intelligence roles.

Be Ready for Behavioral Questions

Behavioral questions are a significant part of the interview process. Prepare to discuss your past experiences, particularly how you’ve handled challenges or failures in projects. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you provide concrete examples that highlight your problem-solving skills and adaptability.

Engage with Your Interviewers

Interviews at Freewheel can sometimes feel disorganized, so take the initiative to engage with your interviewers. Ask clarifying questions if you feel the conversation is veering off-topic or if you need more context. This not only shows your interest but also helps you steer the discussion back to your strengths and relevant experiences.

Showcase Your Communication Skills

Given the collaborative nature of Business Intelligence roles, effective communication is key. During your interviews, focus on clearly articulating your thoughts and ideas. Practice explaining complex technical concepts in a way that is accessible to non-technical stakeholders, as this will demonstrate your ability to bridge the gap between data and decision-making.

Follow Up Thoughtfully

After your interviews, send a thoughtful follow-up email to express your gratitude for the opportunity and to reiterate your interest in the role. Mention specific points from your conversations that resonated with you, which can help reinforce your fit for the position and keep you top of mind for the interviewers.

By following these tailored tips, you can position yourself as a strong candidate for the Business Intelligence role at Freewheel. Good luck!

Experience and Background

1. Describe a data project you worked on from start to finish. What were the challenges, and how did you overcome them?

This question assesses your practical experience in handling data projects and your problem-solving skills.

How to Answer

Discuss a specific project, focusing on the challenges you faced and the strategies you employed to overcome them. Highlight your role and the impact of the project on the organization.

Example

“In my last role, I led a project to analyze customer behavior data. One major challenge was dealing with incomplete datasets. I implemented data cleaning techniques and collaborated with the data engineering team to fill in the gaps. This resulted in a comprehensive analysis that helped the marketing team tailor their campaigns effectively.”

2. How do you prioritize tasks when working on multiple projects?

This question evaluates your time management and organizational skills.

How to Answer

Explain your approach to prioritization, such as using frameworks or tools to assess urgency and importance. Mention how you communicate with stakeholders to align on priorities.

Example

“I use a combination of the Eisenhower Matrix and regular check-ins with my team to prioritize tasks. By categorizing tasks based on urgency and importance, I ensure that I focus on high-impact projects first while keeping stakeholders informed about timelines.”

3. Can you explain a time when you had to present complex data findings to a non-technical audience?

This question tests your communication skills and ability to simplify complex information.

How to Answer

Describe the situation, your approach to simplifying the data, and the outcome of the presentation. Emphasize your ability to engage the audience and make the data relatable.

Example

“I once presented a data analysis on user engagement to the marketing team. I used visual aids and analogies to explain complex metrics, which helped them understand the insights better. The presentation led to actionable strategies that increased user retention by 15%.”

4. What tools and technologies do you prefer for data analysis and why?

This question gauges your technical proficiency and familiarity with industry-standard tools.

How to Answer

Discuss the tools you are proficient in, why you prefer them, and how they have helped you in your previous roles. Mention any relevant certifications or training.

Example

“I primarily use Python and SQL for data analysis due to their versatility and efficiency. Python’s libraries like Pandas and NumPy allow for complex data manipulation, while SQL is essential for querying large datasets. I also have experience with Tableau for data visualization, which helps in presenting findings effectively.”

Technical Skills

1. Describe your experience with SQL. Can you provide an example of a complex query you wrote?

This question assesses your SQL skills and ability to handle complex data retrieval tasks.

How to Answer

Provide a specific example of a complex SQL query you wrote, explaining the context and the outcome. Highlight any advanced SQL techniques you used.

Example

“In my previous role, I wrote a complex SQL query to join multiple tables and aggregate sales data by region and product category. This involved using window functions to calculate running totals, which provided valuable insights for the sales team’s strategy.”

2. How do you handle missing or corrupted data in your analysis?

This question evaluates your data cleaning and preprocessing skills.

How to Answer

Discuss your approach to identifying and handling missing or corrupted data, including any specific techniques or tools you use.

Example

“I typically start by assessing the extent of missing data and its potential impact on the analysis. I use techniques like imputation for small amounts of missing data and consider removing records if the missing data is substantial. I also document my approach to ensure transparency in the analysis process.”

3. Can you explain the difference between supervised and unsupervised learning?

This question tests your understanding of machine learning concepts.

How to Answer

Provide a clear definition of both terms, along with examples of each. Highlight their applications in business intelligence.

Example

“Supervised learning involves training a model on labeled data, where the outcome is known, such as predicting sales based on historical data. Unsupervised learning, on the other hand, deals with unlabeled data to find patterns or groupings, like customer segmentation based on purchasing behavior.”

4. What is your experience with data visualization tools? Which do you prefer and why?

This question assesses your ability to present data visually and your familiarity with visualization tools.

How to Answer

Discuss the visualization tools you have used, your preferred tool, and the reasons for your preference. Mention any specific projects where you utilized these tools.

Example

“I have experience with Tableau and Power BI for data visualization. I prefer Tableau for its user-friendly interface and powerful capabilities in creating interactive dashboards. In a recent project, I used Tableau to visualize sales trends, which helped the management team make informed decisions quickly.”

Behavioral Questions

1. Tell me about a time you failed to deliver a project on time. What did you learn?

This question evaluates your ability to handle setbacks and learn from experiences.

How to Answer

Be honest about the situation, focusing on what led to the delay and the lessons learned. Emphasize your proactive approach to prevent similar issues in the future.

Example

“I once underestimated the time required for data collection in a project, which led to a delay in delivery. I learned the importance of setting realistic timelines and incorporating buffer periods. Since then, I’ve improved my project planning skills and always communicate potential risks to my team.”

2. How do you handle conflicts within a team?

This question assesses your interpersonal skills and ability to work collaboratively.

How to Answer

Describe your approach to conflict resolution, emphasizing communication and collaboration. Provide an example of a conflict you successfully navigated.

Example

“When conflicts arise, I believe in addressing them directly and openly. In a previous project, two team members disagreed on the approach to data analysis. I facilitated a meeting where each could present their perspective, leading to a compromise that combined both ideas. This not only resolved the conflict but also strengthened team cohesion.”

3. Where do you see yourself in five years?

This question gauges your career aspirations and alignment with the company’s goals.

How to Answer

Discuss your professional goals and how they align with the company’s direction. Mention any skills you wish to develop or roles you aspire to.

Example

“In five years, I see myself in a leadership role within the business intelligence field, driving data-driven decision-making at a strategic level. I aim to enhance my skills in data science and machine learning, which I believe will be crucial for advancing in this rapidly evolving industry.”