Yammer, Inc. Data Scientist Interview Questions + Guide in 2025

Yammer, Inc. is a leading social network platform designed to enhance workplace communication and collaboration.

In the Data Scientist role at Yammer, you will be responsible for analyzing complex datasets to derive actionable insights that guide business decisions and improve the user experience. Key responsibilities include conducting exploratory data analysis (EDA), developing predictive models, and utilizing statistical techniques to evaluate hypotheses relevant to user engagement and product performance. This position requires proficiency in programming languages such as Python or R, familiarity with data visualization tools, and strong knowledge of probability and statistics. Ideal candidates will possess a deep understanding of data-driven decision-making processes, exceptional problem-solving skills, and the ability to communicate complex findings in an accessible manner. Additionally, a collaborative mindset aligned with Yammer's commitment to fostering open communication will be crucial for success in this role.

This guide will equip you with essential insights and relevant questions to help you prepare effectively for your interview at Yammer, ensuring you present yourself as a knowledgeable and fitting candidate for the Data Scientist position.

The interview process for a Data Scientist role at Yammer, Inc. is structured to assess both technical skills and cultural fit within the company. The process typically unfolds in several key stages:

1. Initial Phone Screen

The first step is a phone screen, usually lasting around 30 minutes. This interview is conducted by a recruiter or a member of the analytics team. The focus is on understanding your background, skills, and motivations for applying to Yammer. Expect to answer general questions about your experience and to discuss your interest in data science. This stage may also include a few introductory probability questions to gauge your analytical thinking.

2. Technical Phone Interview

If you pass the initial screen, you will be invited to a technical phone interview. This round is more focused on your technical abilities and typically lasts about 30 to 45 minutes. You will be asked to solve probability problems and may be required to demonstrate your thought process in real-time, often by sharing your screen and using your preferred coding environment. Questions may involve statistical concepts, data analysis techniques, and practical applications of data science methodologies.

3. Second Technical Interview

Following the technical phone interview, a second technical interview may be scheduled. This round often includes more complex problem-solving scenarios and may involve case studies or hypothetical situations relevant to the role. You might be asked to analyze a dataset or discuss how you would approach a specific data-related challenge. Expect to engage in discussions about A/B testing, experimental design, and other analytical frameworks.

4. Onsite Interview (or Final Round)

The final stage of the interview process is typically an onsite interview, which may also be conducted virtually. This round consists of multiple interviews with different team members, including data scientists and possibly product managers. Each interview will cover a mix of technical questions, behavioral assessments, and discussions about your past experiences. You may be asked to solve problems on the spot, explain your reasoning, and demonstrate your ability to communicate complex ideas clearly.

Throughout the process, be prepared for a variety of questions that test your understanding of probability, statistics, and data analysis techniques.

Now, let's delve into the specific interview questions that candidates have encountered during their interviews at Yammer, Inc.

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

Prepare for Probability and Analytical Questions

Yammer places a strong emphasis on probability and analytical thinking during their interviews. Be ready to tackle questions that require you to apply probability theory, such as calculating the likelihood of certain outcomes or analyzing scenarios involving random events. Familiarize yourself with common probability problems, such as the birthday paradox or dice roll probabilities, and practice articulating your thought process clearly. This will not only demonstrate your technical skills but also your ability to communicate complex ideas effectively.

Master Exploratory Data Analysis (EDA)

During the interview, you may be given a dataset to analyze. Brush up on your EDA skills, as you might be asked to perform tasks such as summarizing data, identifying trends, and visualizing results. Make sure you are comfortable using tools like Python or R, and be prepared to share your screen to demonstrate your findings. Practice working with sample datasets to refine your approach and ensure you can quickly derive insights during the interview.

Emphasize Problem-Solving Skills

Yammer values candidates who can think critically and solve problems creatively. Be prepared to discuss how you would approach hypothetical scenarios, such as evaluating the effectiveness of different office layouts or analyzing user behavior trends. Use the STAR (Situation, Task, Action, Result) method to structure your responses, showcasing your analytical thinking and decision-making process.

Communicate Clearly and Confidently

Given that some interviewers may not be native English speakers, clarity in communication is crucial. Practice explaining your thought process and solutions in a straightforward manner. If you don’t understand a question, don’t hesitate to ask for clarification. This shows that you are engaged and willing to ensure mutual understanding, which is a valuable trait in a collaborative environment.

Understand the Company Culture

Yammer's culture is likely to be collaborative and dynamic, given its focus on communication and teamwork. Familiarize yourself with their values and mission, and think about how your personal values align with theirs. During the interview, express your enthusiasm for working in a team-oriented environment and your commitment to contributing positively to the company culture.

Follow Up Professionally

After your interview, send a thank-you email to express your appreciation for the opportunity to interview. This not only reinforces your interest in the position but also demonstrates professionalism and good communication skills. If you don’t hear back within a reasonable timeframe, consider sending a polite follow-up email to inquire about the status of your application.

By preparing thoroughly and approaching the interview with confidence and clarity, you can position yourself as a strong candidate for the Data Scientist role at Yammer. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Scientist interview at Yammer, Inc. The interview process will likely assess your understanding of statistical concepts, data analysis skills, and your ability to apply these in real-world scenarios. Be prepared to demonstrate your analytical thinking and problem-solving abilities through both theoretical questions and practical applications.

Statistics & Probability

1. What is the probability that in a room full of k people, at least 2 people will have the same birthday?

Understanding the birthday problem is a classic probability question that tests your grasp of combinatorial principles.

How to Answer

Explain the concept of complementary probability and how to calculate the likelihood of at least two people sharing a birthday by first calculating the probability that no one shares a birthday.

Example

“The probability can be calculated using the complement principle. If we assume 365 days in a year, the probability that no two people share a birthday is calculated by multiplying the probabilities for each person added to the room. Thus, for k people, the probability is 1 - (365/365) * (364/365) * ... * ((365-k+1)/365).”

2. If you roll three 6-sided dice, what is the probability that all three dice show different numbers?

This question tests your ability to apply probability rules in a straightforward scenario.

How to Answer

Discuss the total outcomes and the favorable outcomes for this scenario, demonstrating your understanding of permutations.

Example

“The total number of outcomes when rolling three dice is 6^3. The number of favorable outcomes where all three dice show different numbers is 6 * 5 * 4. Therefore, the probability is (6 * 5 * 4) / (6^3) = 20/36 or 5/9.”

3. If you get $1 per dot on the upturned face of a rolled die, what is your expected earnings?

This question evaluates your understanding of expected value.

How to Answer

Explain how to calculate expected value by considering all possible outcomes and their probabilities.

Example

“The expected value is calculated as (1/6)(1) + (1/6)(2) + (1/6)(3) + (1/6)(4) + (1/6)(5) + (1/6)(6) = 3.5. Therefore, my expected earnings would be $3.5.”

4. Describe a method to investigate which office layout design (open vs. closed) is better.

This question assesses your ability to design an analytical approach to a real-world problem.

How to Answer

Outline a structured approach, including hypothesis formulation, data collection, and analysis methods.

Example

“I would start by formulating a hypothesis regarding productivity levels in each layout. Then, I would collect data through surveys and performance metrics, followed by conducting an A/B test to analyze the impact of each layout on employee performance and satisfaction.”

5. How would you approach a problem with no clear solution?

This question tests your problem-solving skills and creativity in data analysis.

How to Answer

Discuss your thought process in breaking down the problem and exploring alternative solutions.

Example

“I would first define the problem clearly and gather as much data as possible. Then, I would brainstorm potential solutions, even unconventional ones, and test them iteratively to see which approach yields the best results, while remaining open to adjusting my strategy based on findings.”

Data Analysis & Modeling

1. Given a dataset, how would you perform exploratory data analysis (EDA)?

This question evaluates your practical skills in data analysis.

How to Answer

Outline the steps you would take to understand the dataset, including visualizations and summary statistics.

Example

“I would start by loading the dataset and checking for missing values. Then, I would generate summary statistics and visualizations such as histograms and box plots to understand the distribution of variables. Finally, I would look for correlations and patterns that could inform further analysis or modeling.”

2. How would you model a situation where you suspect a spike in user uploads is due to a specific event?

This question assesses your ability to connect data analysis with real-world events.

How to Answer

Discuss how you would identify the event and analyze its impact using statistical methods.

Example

“I would first identify the date of the spike and research any events that occurred around that time. Then, I would use time series analysis to compare upload rates before and after the event, controlling for other variables to isolate the effect of the event on user behavior.”

3. Can you explain the concept of A/B testing and how you would implement it?

This question tests your understanding of experimental design.

How to Answer

Describe the process of setting up an A/B test, including control and treatment groups.

Example

“A/B testing involves splitting a sample into two groups: one that receives the treatment and one that does not. I would define clear metrics for success, randomly assign users to each group, and analyze the results using statistical tests to determine if the treatment had a significant effect.”

4. What techniques would you use to handle missing data in a dataset?

This question evaluates your data cleaning skills.

How to Answer

Discuss various methods for dealing with missing data, including imputation and deletion.

Example

“I would first assess the extent and pattern of missing data. Depending on the situation, I might use imputation techniques such as mean or median substitution, or more advanced methods like K-nearest neighbors. If the missing data is not substantial, I might also consider simply removing those records.”

5. How do you ensure the validity and reliability of your data analysis?

This question assesses your understanding of data integrity.

How to Answer

Explain the steps you take to validate your data and ensure your analysis is sound.

Example

“I ensure validity by cross-referencing data sources and using established methods for data collection. For reliability, I would conduct repeat analyses and use statistical tests to confirm that my findings are consistent across different samples or time periods.”