Known Data Analyst Interview Questions + Guide in 2025

Known is a forward-thinking company dedicated to leveraging data to enhance media campaigns and deliver actionable insights for clients.

As a Data Analyst at Known, you will play a pivotal role in optimizing media campaigns through data-driven decision-making and analytical strategies. Your core responsibilities will include analyzing large datasets to derive meaningful insights, validating data through audits, and developing new analytical methodologies to enhance campaign performance. Strong proficiency in SQL and Python is essential, as you'll be expected to craft complex queries, perform statistical analyses, and help automate processes. Familiarity with A/B testing and digital advertising metrics will be critical, enabling you to design experiments that drive results. A keen sense of curiosity and critical thinking will empower you to explore innovative approaches while collaborating with other data professionals. This role aligns with Known’s commitment to excellence and efficiency, fostering a culture where insights are not just gathered but transformed into actionable strategies.

This guide will equip you with the knowledge and confidence needed to excel in your interview for the Data Analyst role at Known, ensuring you can showcase your expertise and alignment with the company's values.

The interview process for a Data Analyst position at Known is structured to assess both technical and interpersonal skills, ensuring candidates are well-rounded and fit for the role.

1. Initial Technical Interview

The first step typically involves a 30-minute technical interview conducted over the phone or via video call. This session focuses on assessing your foundational knowledge in data analysis, particularly your proficiency in SQL and Python. Expect to encounter questions that may include numerical reasoning and basic coding challenges. This round serves as a preliminary filter to gauge your technical capabilities and problem-solving skills.

2. HR Interview

Following the technical interview, candidates usually participate in a 30-minute HR interview. This session is designed to evaluate your cultural fit within the company and your alignment with Known's values. You will discuss your work experience, motivations for applying, and how you handle various workplace scenarios. Be prepared to articulate your career goals and how they align with the company's mission.

3. Technical Rounds with Data Science Team

Candidates who successfully pass the initial rounds are invited to a series of three technical interviews with members of the Data Science team. Each of these interviews lasts approximately 30 minutes and delves deeper into your technical expertise and past projects. You may be asked to describe specific machine learning projects you've worked on, explain complex concepts like p-values to a non-technical audience, and discuss your experience with A/B testing and statistical analysis. This is also an opportunity to showcase your analytical thinking and problem-solving abilities.

4. Final Interview with Leadership

The final stage of the interview process typically involves a more in-depth discussion with senior leadership, such as the VP of Data Science. This round may include both technical and behavioral questions, focusing on your ability to contribute to the team and the organization as a whole. Expect to discuss your favorite machine learning algorithms, your approach to data-driven decision-making, and how you can help optimize media campaigns at Known.

As you prepare for these interviews, consider the specific skills and experiences that will be most relevant to the role. Next, we will explore the types of questions you might encounter during this process.

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

Understand the Interview Structure

The interview process at Known typically consists of multiple rounds, including technical and HR interviews. Be prepared for a 45-minute technical interview followed by a 30-minute HR interview, and then additional rounds with team members. Familiarize yourself with the structure so you can manage your time and energy effectively throughout the process.

Master SQL and Python

Given the emphasis on SQL and Python in the role, ensure you are well-versed in both. Practice SQL queries that involve complex joins, subqueries, and window functions. For Python, focus on coding challenges that may involve data manipulation and analysis. Being able to demonstrate your technical skills confidently will set you apart.

Prepare for Behavioral Questions

Expect behavioral questions that assess your problem-solving abilities and teamwork. Be ready to discuss your previous work experiences, particularly those that relate to data analysis in advertising or marketing. Use the STAR (Situation, Task, Action, Result) method to structure your responses, highlighting your contributions and the impact of your work.

Showcase Your Analytical Skills

As a Data Analyst, your ability to derive insights from data is crucial. Be prepared to discuss specific projects where you utilized analytical methodologies, such as A/B testing or statistical analysis. Explain your thought process and the outcomes of your analyses, demonstrating how your insights led to actionable strategies.

Communicate Complex Concepts Clearly

You may be asked to explain technical concepts, such as p-values or machine learning algorithms, to non-technical stakeholders. Practice simplifying complex ideas into layman's terms. This skill is essential for effectively communicating your findings and recommendations to clients and team members.

Emphasize Curiosity and Continuous Learning

Known values candidates who exhibit curiosity and a desire to improve processes. Be prepared to discuss how you stay updated with industry trends and your approach to learning new analytical techniques or tools. This mindset will resonate well with the company culture and demonstrate your commitment to growth.

Ask Insightful Questions

At the end of your interviews, you will likely have the opportunity to ask questions. Use this time to inquire about the team dynamics, ongoing projects, or the company’s approach to data-driven decision-making. Thoughtful questions will show your genuine interest in the role and help you assess if Known 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 Known. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Known. The interview process will likely focus on your technical skills, particularly in SQL and Python, as well as your understanding of machine learning concepts and statistical analysis. Be prepared to discuss your previous work experience and how it relates to the role, especially in the context of media analytics and campaign optimization.

Technical Skills

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

Discuss the purpose of each join type and provide examples of when you would use them in a query.

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 instance, if I want to list all customers and their orders, I would use a LEFT JOIN to ensure I include customers who may not have placed any orders.”

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

Performance optimization is key in data analysis roles.

How to Answer

Mention techniques 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. Then, I might add indexes to frequently queried columns or rewrite the query to reduce complexity, ensuring it retrieves only the necessary data.”

3. Describe a machine learning project you have worked on.

This question assesses your practical experience with machine learning.

How to Answer

Provide a brief overview of the project, your role, and the outcome.

Example

“I worked on a project to predict customer churn using logistic regression. I collected and cleaned the data, selected relevant features, and built the model, which improved our retention strategy by identifying at-risk customers with 85% accuracy.”

4. What is a p-value, and how would you explain it to a non-technical person?

Understanding statistical concepts is essential for data analysis.

How to Answer

Define the p-value and its significance in hypothesis testing, using simple language.

Example

“A p-value measures the strength of evidence against the null hypothesis. If I were explaining it to a non-technical person, I would say it helps us understand whether our results are due to chance or if they are statistically significant.”

5. How do you approach A/B testing?

A/B testing is a common method for optimizing campaigns.

How to Answer

Discuss the steps involved in designing and analyzing an A/B test.

Example

“I start by defining a clear hypothesis and selecting key performance indicators. Then, I randomly assign users to control and test groups, ensuring the test runs long enough to gather significant data. Finally, I analyze the results to determine if the changes had a meaningful impact.”

Behavioral Questions

1. Describe a technical project you have been a part of. Explain it to me.

This question evaluates your ability to communicate complex ideas clearly.

How to Answer

Summarize the project, your contributions, and the impact it had.

Example

“I was part of a team that developed a dashboard for real-time campaign performance tracking. I was responsible for data extraction and visualization. The dashboard allowed our marketing team to make data-driven decisions quickly, leading to a 20% increase in campaign efficiency.”

2. What kind of environment do you work best in?

This question helps assess cultural fit within the team.

How to Answer

Reflect on your preferred work style and how it aligns with the company’s culture.

Example

“I thrive in collaborative environments where team members share ideas and feedback. I believe that open communication fosters innovation, and I enjoy working with others to solve complex problems.”

3. Why do you want to work at Known?

This question gauges your interest in the company and role.

How to Answer

Discuss what attracts you to the company and how your skills align with their mission.

Example

“I admire Known’s commitment to leveraging data for impactful media campaigns. I believe my analytical skills and experience in digital advertising can contribute to optimizing client performance and driving results.”

4. Are there any questions I didn't ask that you wish I had asked?

This question allows you to highlight any important aspects of your experience.

How to Answer

Use this opportunity to discuss a relevant project or skill that hasn’t been covered.

Example

“I’d love to share more about my experience with data visualization tools like Tableau, which I used to create interactive dashboards that helped stakeholders understand complex data insights more easily.”

5. Tell me about your work experience.

This question provides a chance to summarize your professional background.

How to Answer

Highlight key roles, responsibilities, and achievements relevant to the position.

Example

“I have over three years of experience as a data analyst in the advertising sector, where I focused on campaign performance analysis and optimization. My work involved using SQL and Python to analyze large datasets, which led to actionable insights that improved our clients’ ROI.”