Integral Ad Science Data Analyst Interview Questions + Guide in 2025

Integral Ad Science (IAS) is a leading global technology company that specializes in media measurement and optimization solutions for the advertising industry.

As a Data Analyst at IAS, you will play a crucial role in shaping data-driven strategies that enhance the effectiveness of advertising verification products, such as brand safety and fraud detection. Your responsibilities will include analyzing complex datasets from various sources, including social networks and mobile applications, to derive actionable insights that influence product development and drive business growth. You will work closely with cross-functional teams, including data engineering and business operations, to prioritize initiatives, set goals, and ensure alignment with company objectives. Exceptional analytical skills, proficiency in data querying (SQL), and experience with programming languages like Python are essential for success in this role. Furthermore, the ability to communicate technical information effectively to both technical and non-technical stakeholders is vital, as you will help define key performance indicators (KPIs) and provide clear recommendations based on your analyses.

This guide will equip you with the knowledge and insights needed to excel in your interview for the Data Analyst position at IAS, ensuring that you present yourself as a well-prepared and confident candidate.

The interview process for a Data Analyst position at Integral Ad Science is structured to assess both technical skills and cultural fit within the organization. It typically consists of several key stages:

1. Application and Initial Screening

The process begins with submitting an application, which is followed by an initial phone screening with a recruiter. This conversation focuses on your background, experience, and motivation for applying to IAS. The recruiter will also provide insights into the company culture and the specifics of the Data Analyst role.

2. Pre-Employment Assessments

Candidates who pass the initial screening will be required to complete two proctored pre-employment assessments: a cognitive assessment and a personality assessment. These assessments are conducted online via a proctoring service and are considered critical in evaluating your analytical thinking and alignment with the company’s values.

3. Technical Assessment

Following the assessments, candidates will be given a technical assessment that must be completed within 48 hours. This assessment is designed to evaluate your proficiency in data querying, analysis, and relevant technical skills, such as SQL and Python.

4. Team Interview

If you successfully complete the technical assessment, you will be invited to a team interview. This session typically lasts around 45 minutes and involves discussions with team members about your technical skills, past experiences, and how you approach data analysis. Be prepared to discuss specific projects and how your contributions have driven results.

5. Stakeholder Wrap-Up

The final step in the interview process involves a wrap-up discussion with stakeholders. During this meeting, you may be asked to talk about a particular project you have worked on, showcasing your ability to communicate data insights effectively and your understanding of how data can influence business decisions.

As you prepare for your interview, it’s essential to familiarize yourself with the types of questions that may arise during these stages.

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

Understand the Assessment Process

Integral Ad Science places significant emphasis on their pre-employment assessments, particularly the cognitive and personality assessments. Familiarize yourself with the types of questions that may be asked in these assessments, as they are considered crucial in the selection process. Practice cognitive reasoning tests and reflect on your personality traits to ensure you can articulate how they align with the company’s values and culture.

Prepare for Technical Proficiency

As a Data Analyst, you will be expected to demonstrate strong technical skills, particularly in SQL and Python. Brush up on your SQL querying abilities, focusing on complex queries and data manipulation techniques. Additionally, practice using Python libraries such as Pandas and NumPy to analyze datasets. Be prepared to discuss specific projects where you utilized these skills to drive insights or solve problems.

Showcase Your Analytical Mindset

During the interview, emphasize your analytical skills and your ability to derive actionable insights from data. Be ready to discuss how you have previously identified trends, quantified opportunities, or solved challenges using data analysis. Use specific examples to illustrate your thought process and the impact of your work on product development or business strategy.

Communicate Effectively with Stakeholders

Integral Ad Science values clear communication across technical and non-technical teams. Prepare to discuss how you have successfully communicated complex data concepts to diverse audiences. Highlight your experience in collaborating with various stakeholders, such as sales and marketing teams, and how you translated data findings into meaningful narratives that informed business decisions.

Engage with the Team

The interview process includes a team interview where you will have the opportunity to ask questions. Use this time to engage with the team by asking insightful questions about their current projects, challenges they face, and how the data analyst role contributes to their success. This not only shows your interest in the position but also helps you assess if the team dynamics align with your working style.

Align with Company Culture

Integral Ad Science emphasizes trust, transparency, and collaboration. Reflect on how your personal values align with these principles and be prepared to discuss them during the interview. Share examples of how you have fostered collaboration in previous roles or how you have contributed to a culture of transparency and trust within your teams.

Follow Up Thoughtfully

After the interview, consider sending a thoughtful follow-up email to express your gratitude for the opportunity to interview. Use this as a chance to reiterate your enthusiasm for the role and the company, and to briefly mention any key points from the interview that you found particularly engaging. This will leave a positive impression and reinforce your interest in joining the team.

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

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Integral Ad Science. The interview process will likely assess your technical skills in data analysis, your ability to communicate insights effectively, and your understanding of the advertising technology landscape. Be prepared to demonstrate your analytical thinking, problem-solving abilities, and how you can leverage data to drive business decisions.

Technical Skills

1. Can you explain the process you follow for data cleaning and preparation?

Data cleaning is a critical step in data analysis, and interviewers want to know your approach to ensuring data quality.

How to Answer

Discuss the specific techniques you use for data cleaning, such as handling missing values, outlier detection, and data normalization. Highlight any tools or programming languages you prefer for these tasks.

Example

“I typically start by assessing the dataset for missing values and outliers. I use Python libraries like Pandas to fill in missing values based on the context of the data, and I apply z-scores to identify outliers. After cleaning, I ensure the data is normalized to maintain consistency across different data points.”

2. Describe a complex SQL query you have written and its purpose.

SQL proficiency is essential for a Data Analyst role, and this question assesses your ability to write complex queries.

How to Answer

Provide a specific example of a SQL query you wrote, explaining the problem it solved and the logic behind it. Mention any joins, subqueries, or aggregations used.

Example

“I once wrote a complex SQL query to analyze customer purchase behavior. The query involved multiple joins across several tables to aggregate data on customer demographics and purchase history. I used a CTE to simplify the logic and included window functions to rank customers based on their total spend, which helped the marketing team target high-value customers effectively.”

3. How do you approach data visualization, and what tools do you prefer?

Data visualization is key to communicating insights, and interviewers want to know your preferred methods and tools.

How to Answer

Discuss your philosophy on data visualization, the importance of clarity, and the tools you are proficient in, such as Looker or Power BI.

Example

“I believe that effective data visualization should tell a story and highlight key insights. I prefer using Looker for its flexibility and ability to create interactive dashboards. I focus on using clear labels and color schemes to ensure that the data is easily interpretable by stakeholders.”

4. Can you give an example of how you used data to influence a business decision?

This question assesses your ability to apply data analysis in a real-world context.

How to Answer

Share a specific instance where your analysis led to actionable insights that impacted a business decision. Highlight the data you used and the outcome.

Example

“In my previous role, I analyzed user engagement metrics for a new product feature. My analysis revealed that users were dropping off at a specific point in the onboarding process. I presented these findings to the product team, and we implemented changes that improved user retention by 25% within a month.”

Analytical Thinking

5. How do you prioritize multiple data requests from different stakeholders?

This question evaluates your organizational skills and ability to manage competing priorities.

How to Answer

Explain your approach to prioritization, including how you assess the urgency and impact of each request.

Example

“I prioritize data requests based on their potential impact on business objectives and deadlines. I maintain open communication with stakeholders to understand their needs and set realistic timelines. If multiple requests are urgent, I assess which analysis will provide the most value to the organization and tackle those first.”

6. Describe a time when you had to explain a complex data concept to a non-technical audience.

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

How to Answer

Provide an example of a situation where you successfully communicated a complex concept, focusing on how you tailored your explanation to the audience.

Example

“I once had to explain the concept of A/B testing to the marketing team. I used simple analogies and visual aids to illustrate how we could compare two versions of an ad to see which performed better. By breaking it down into relatable terms, the team was able to grasp the concept and apply it to their campaigns.”

7. What metrics do you consider most important when evaluating the success of an advertising campaign?

This question assesses your understanding of key performance indicators (KPIs) in the advertising industry.

How to Answer

Discuss the metrics you believe are critical for evaluating campaign success, such as ROI, CTR, and conversion rates, and explain why they matter.

Example

“I consider metrics like ROI and conversion rates to be crucial for evaluating advertising success. ROI helps us understand the financial return on our investment, while conversion rates indicate how effectively our ads are driving desired actions. Together, they provide a comprehensive view of campaign performance.”

8. How do you stay updated with the latest trends in data analytics and advertising technology?

This question gauges your commitment to continuous learning and professional development.

How to Answer

Share the resources you use to stay informed, such as industry blogs, webinars, or professional networks.

Example

“I regularly follow industry blogs like AdExchanger and attend webinars hosted by analytics platforms. I also participate in online forums and communities where professionals share insights and best practices. This helps me stay current with trends and innovations in data analytics and advertising technology.”