Google Data Scientist Interview Questions are challenging and specific to Google's data products. Google has a high hiring bar for data scientists. You must demonstrate your hands-on experience in data science and machine learning projects to nail a Google data scientist interview.
Data Science is an exponentially rising technology, and Google has abundant job opportunities for professional data scientists globally.
You must demonstrate your technical and non-technical skills while answering Google Data Scientist interview questions to outperform the competition and create a lasting impact on the recruiting panel. The following Google Data Scientist interview questions will help you ace your next technical interview and land your dream job.
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Here's what we'll cover:
- What Is the Google Data Scientist Interview Process Like?
- Technical Skills Required to Crack Google Data Scientist Interview
- Google Data Scientist Interview Questions
- Questions to Ask the Interviewer at Google
- How to Stand Out in Google Data Scientist Interviews?
- FAQs on Google Data Scientist Interview Questions
What Is the Google Data Scientist Interview Process Like?
Before you practice the most anticipated data scientist interview questions at Google, you should be familiar with the interview process. Here is a breakdown of the various stages of the Google data scientist interview process to assist you in developing your tech interview preparation.
The Initial Phone Screen Round
Duration: 30 minutes to 1 hour
You will first have to appear for the phone screen round, which is similar to other top tech companies. It usually takes place over video chat on Google Hangouts/ Google Meet.
In this round, the recruiter will confirm your basic knowledge, proficiency in programming, qualification, and work experience. The recruiter will also inquire about your willingness and availability as per Google's requirements.
The Coding/Technical Screen
Duration: 1 hour to 1.5 hours
The technical screen round is held via video conference with data science experts. This round will focus on your technical skills and abilities. The Google data scientist interview questions asked in this round cover various topics, such as Statistics, Python, Machine Learning, Big Data, SQL, A/B Testing, NoSQL, and more. You will have to answer:
- Question on previous data science-based projects
- Situational questions
- A statistics question (computational stats)
- Coding question (on a shared code editor)
On-site Interview - The Googleyness Screener
Duration: 45 minutes per round
Once you have cleared the two initial rounds, the final stage is the Googleyness screener. This is an on-site interview, and it consists of five rounds with data scientists, business analysts, and other members of the data science department as your interviewers. These rounds have the most challenging Google data scientist interview questions.
The five rounds will cover:
- Computational Statistics and Machine Learning (56%)
- Product Interpretation ( 9%)
- Behavioral Questions (9%)
- Coding (26%)
Google interviewers will evaluate all the abilities that can prove you a culture fit via Google data scientist interview questions.
Technical Skills Required to Crack the Google Data Scientist Interview
As a data scientist, you should have a master's degree in fields such as Statistics, Applied Mathematics, Information Technology, or other relevant branches of Science and Engineering. Google values some relevant work experience in programming, data handling, engineering, or statistics. Additionally, if you are applying for a data scientist role at Google, you must work on the following technical skills:
- Statistical languages such as R or Python
- Data visualization including knowledge in ggplot, d3.js and Matplotlib, and Tableau
- Soft skills such as communication, adaptability, problem-solving, strategic management are the most sought-after skills at Google Data Scientist interviews.
Google Data Scientist Interview Questions
You ought to be thorough on a wide range of topics for Google data scientist interview questions. You won't encounter the same questions word by word in your Google data scientist interview; the basic requirement is to decipher inherent patterns in these questions. Your goal is to practice the most anticipated Google data scientist interview questions so that you are able to solve new problems that employ similar logic and approaches. Here are some important questions that you must practice.
Google Data Scientist Interview Questions on Machine Learning and AI
- What do you understand by supervised and unsupervised machine learning?
- What is the difference between the bagged model and boosted model?
- How would you differentiate between K-mean and EM?
- How would you encode a categorical variable with thousands of distinct values?
- What steps will you take to design and build the recommendation algorithm for a type-ahead search for Google?
- What methods would you use to detect anomalies in AI?
- What do you understand about the Rectified Linear Unit in Machine Learning?
- What is the AdaGrad algorithm in Machine Learning?
- What is AUC? What are evaluation metrics in AI and Machine Learning?
- What are the applications of Feature Selection in AI?
Google Data Scientist Interview Questions on Statistics and Probability
- There are 20 pink and 20 white balls in a box. There is another box with 40 pinks and 40 white balls. If you have to pick two balls at random from any one of the two boxes, which box has the higher probability of satisfying your requirements?
- What are the steps to test the applicability of the Gaussian mixture model?
- How would you simulate a bivariate normal?
- How can you derive the variance of a distribution?
- How can you build estimators for medians?
- What do you understand about a probability distribution that is not normal? How would you apply it?
- For highly correlated two predictors, what are the confidence intervals of the coefficients? How would that affect the coefficients in the logistic regression?
- Differentiate K-mean and Gaussian mixture models?
- Write a derivation for the equations for GMM.
- How to assess if a given coin is biased? What do the p-values in high dimensional linear regression tell you?
- What is the derivative of 1/x?
- If you have ten coins and you toss each coin ten times. Would you change your approach to the way you assess the fairness of coins?
- What steps help remove bias in A/B Testing?
Google Data Scientist Interview Questions on Coding
As a Google data scientist, you will have to use coding every day to mine datasets and generate insights. The Google data scientist interview questions on coding include SQL, data analysis, and Python coding questions.
You must practice as many Google data scientist interview questions on data structures and algorithms as you can to ace this round of interviews. The important topics for coding rounds are:
- Binary Tree Example Code
- Strings and Arrays
- Linked List
- Bit Manipulation
- Small Programs (string, memory functions)
Sample Google data scientist interview questions on coding:
- In a normal distribution, write a function to generate N samples. Also, plot a histogram.
- Write a program to read a text file using a series of tweets. Output- two text files where the first one lists all the unique words in the tweets and the number of words that get repeated. Your second will contain the average number of unique words in all the tweets.
- Given two data frames where one contains information about addresses, and the other data frame has relationships between various cities and states. Write a function to create a single data frame with complete addresses (format-street, city, state, zip code).
- For a given percentile threshold and N samples, write a function to simulate a truncated normal distribution.
You can practice more coding questions on the problems page and also check your answers.
Data Science Interview Questions on Product Sense
Here are some additional Google data scientist interview questions for you to practice.
- How could you test if a metric has increased on a change you made in a Google app?
- How do you detect inappropriate content on YouTube?
- How would you evaluate if upgrading the android app enhances searches?
- How to design a customer satisfaction survey?
- How would you account for users' likes on videos?
- What Data Science-based product will you build for Google and why?
Some Additional Practice Questions for Data Scientists
- Why would you choose GBM over logistic regression?
- How can NoSQL databases be better than SQL databases?
- What procedure will you follow to resolve the issue of bias in case of removal of missing values from a database?
- How will you test the changes you have made to a mobile app for a business firm?
- What is caching in Data Science? Explain how it works.
- What do you understand about Hadoop architecture?
- What are the methods and techniques for anomaly detection?
- How do you think Data Science can contribute to Smart City development?
Google Behavioral Interview Questions
Google data scientist interview questions assess your personality traits as well. The behavioral questions are designed to determine how you would react in similar workplace situations. Regardless of the role or position you apply for, you must complete a mandatory behavioral round. Your responses to these questions have a significant impact on the outcome of the interview.
Here are some behavioral questions asked at Google:
- Describe a past data science project you worked on.
- How do you prioritize tasks when working on many different projects?
- How do you complete multiple projects under tight time constraints?
- What career goals do you have? How do you plan to achieve them?
- Do you have a favorite Google product? What do you love about it?
- Describe a time when a project you were working on wasn't successful. What did you learn?
- How would you handle an uncooperative co-worker?
- What is the best way to maintain a work-life balance?
- What makes you interested in this Data Scientist position at Google?
- What is it about Google's culture that you like the most?
Questions to Ask the Interviewer at Google
It is critical that you understand that an interview is more than just a chance for the hiring manager to ask questions — it is also your opportunity to inquire about some crucial details that will help you decide if a job is a good fit for you.
In a data scientist interview at Google, you can ask a few questions that will enhance your value as a potential candidate while also reflecting your enthusiasm for the position. Here are some questions you could ask the interviewer:
- What training programs are available to your data scientists?
- Where have successful data scientists previously in this position progressed to?
- What metrics will my performance be evaluated against?
- Can you tell me about the team I'll be working with?
- Is there anything I can provide that would be helpful?
How to Stand Out in Google Data Scientist Interviews
You should be well-prepared to answer Google data scientist interview questions. Here is how you can ace the data scientist interview:
- To succeed in the Google data scientist interview, you must have a diverse skill set. The above Google data scientist interview questions provide a taste of the wide range of topics covered in the interviews.
- You should prepare for situation-based questions asked in the final rounds of on-site interviews by taking mock interviews. You must take your time answering each question in order to effectively demonstrate analytical and problem-solving skills. Your responses should demonstrate your rational mindset and critical thinking skills.
- You should improve your technical skills and your communication, analytical, and decision-making abilities.
- It is critical to have a thorough understanding of and familiarity with Google products. Your deep understanding of Google's business line and the organization's timeline can help you outperform other candidates.
- Refresh your knowledge of programming and database languages. You should be well-versed in fundamental concepts and advanced problems. Google has high expectations for its new hires. You must gain experience with a programming language, such as R or Python. It is best to start with the fundamentals, such as working on the syntax and commands for the specific language, and then progress to algorithm design and development.
- If you are applying for a senior data scientist position, aspects such as strategy development and management are explored in the Google data scientist interview questions. You can practice such question sessions with your colleagues or friends to refine your skills.
FAQs on Google Data Scientist Interview Questions
Q1. Do Google Data Scientist interview questions include coding?
The phone interviews usually focus on the fundamental concepts, but Google data scientist interviews have statistical questions and coding too. You will be coding live on a shared document in a programming language of your choice. You must clearly communicate your steps and reasoning as you work on the Google data scientist interview questions.
Q2. How to prepare for Google Data Scientist behavioral questions?
You must create a list of your relevant data science projects and accomplishments that you can talk about while answering behavioral questions. Practice the most common Google data science interview questions and also take a few mock interviews.
Q3. How to answer Google Data Scientist interview questions on product sense?
When you answer Google data scientist interview questions on product sense, you’ll need to apply your statistical and coding skills. You must exhibit your technical knowledge that will help test and drive business and product decisions.
Q4. Are Google data science interviews hard to crack?
Google Data scientist interviews are difficult. The questions are tricky, Google-specific, and based on a wide range of topics. Although, proper preparation can help you ace the interview and grab an offer from Google.
Q5. What does a Google data scientist do?
A Google Data Scientist is responsible for improving and analyzing Google's products. Data Scientists collaborate with analysts and engineers to solve a wide range of problems. A Data Scientist's responsibilities at Google also include handling large and complex data sets.
How to Prepare for Your Next Google Data Scientist Interview
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