How to Ace Data Scientist Interviews at Google

Data scientists at Google work on a wide range of teams, products, and features, from improving advertising effectiveness to optimizing network infrastructure.

The Google data science position is primarily an analytics position that focuses on metrics and experimentation. This is distinct from Google's machine learning and product analyst roles, which are more focused on the engineering or product sides, respectively. Google used to call the data science role a quantitative analyst before changing it to data science to attract more talent.

Data scientist interviews at Google are relatively easy to get through. The questions are a little tricky and they are mostly related to Google-specific topics. The good news is that proper preparation can help candidates to increase their chances of getting a job offer from Google (or Google Cloud). 

The ultimate success guide, with sample questions, links to solutions, and a preparation plan, will help the candidates land that Google data scientist role.

Candidates who are applying for the position of data scientist at Google must know that the entire process would take 3 - 6 weeks. This process involves the following steps: 

• Applications and Recommendations
• Recruiter screening (30 minutes)
• Technical screening (45-60 minutes)
• In-person interviews (5 interviews, 45 min each)

Qualifications Required to Qualify Google Interview

The qualifications required to qualify for the Google interview are given below: 

• Master's or doctorate degree in Statistics, Computer Science, Bioinformatics, Computational Biology, Engineering, Physics, Applied Mathematics, Economics, Operations Research, or a related quantitative discipline, or equivalent practical experience
• Advanced experience with statistical software (e.g., MATLAB, Panda, Colab, S-Plus, SAS, and so on), programming languages such as Python, R, C++, and/or Java, and database languages (e.g., SQL) and management systems.
• Data science experience with a focus on business analytics, including designing and building statistical models, visualization, machine learning, digital attribution, forecasting, optimization, and predictive analytics.
• Advanced statistical concepts and hands-on experience with machine learning on large datasets are required.
• Experience deploying large-scale data science solutions using big data and cloud platforms.
• Problem framing, problem-solving, project management, and people management abilities must be demonstrated.

Google Data Scientist Interview Process

Following the application review, a Google recruiter will contact the candidate via email with a pre-screen questionnaire only if the candidates pass their initial screening after submitting their application on the Google careers page.

Recruiter Connection

The first screening is typically a 30-minute phone interview with a recruiter during which they outline the job role and duties. During this interview, they will have the opportunity to speak with the recruiter, and the recruiter will learn more about their skills.

This preliminary interview is similar to that of other tech companies such as Amazon, Apple, and Microsoft. A recruiter may approach the candidates based on their LinkedIn profile or because someone he or she knows introduced them to the company. However, it is always advisable to message recruiters on LinkedIn and apply for Google Data Scientist job opportunities through Google's careers website.

Technical Evaluation

Typically, the technical screen is conducted via video conferencing with one of Google's Data Scientists. The questions in this interview generally cover experimental design, statistics, and probability.

There will also be some questions about machine learning, AI, deep learning, data science-based reasoning, and coding (A/B testing, Python, SQL, and Java).

The interviewer may also delve into the technical aspects of the candidate’s previous research and work experience, discussing what problems they encountered and how they solved them.

On-Site Interview with Google

The onsite interview is the final stage of the Google Data scientist interview process. It consists of five 45-minute interviews with professionals ranging from product managers to data scientists and business leaders.

In addition to technical and situational questions, this final round will assess your leadership qualities, how they deal with workplace ambiguity, and whether they will be a culture fit.

Three quick ideas for the onsite round:

• Explain how to approach the problem rather than just providing the solution.
• Feel free to ask the interviewer to clarify any points.
• Prepare an answer to the answer "Why do you want to join Google?" question from the company's human resources department.

What Happens Next?

Google will compile and review the application and interview materials after the interviews are conducted. Google considers a number of factors before making a decision. Then they will make you an offer if they believe you are the best fit candidate for the job role. Following your acceptance of the offer, the Google onboarding team will assist you with remuneration, benefits, badges, insurance, and other details.

Some Popular Data Scientist Questions on Google

1. Why would you choose GBM over logistic regression? 
2. How can NoSQL databases be better than SQL databases? 
3. What procedure will you follow to resolve the issue of bias in case of removal of missing values from a database? 
4. How will you test the changes you have made to a mobile app for a business firm?
5. What is caching in Data Science? Explain how it works. 
6. What do you understand about Hadoop architecture? 
7. What are the methods and techniques for anomaly detection?
8. How do you think Data Science can contribute to Smart City development?

How to Stand Out for Data Scientist Interview at Google

To answer Google data scientist interview questions, you should be well prepared. Here's how to ace your data scientist interview:

• You must have a diverse skill set to succeed in the Google data scientist interview. The Google data scientist interview questions listed above are just a sampling of the topics covered in the interviews.
• Mock interviews can help you prepare for situation-based questions asked in the final rounds of on-site interviews. To effectively demonstrate analytical and problem-solving skills, you must take your time to answer each question. Your responses should demonstrate a rational mindset as well as critical thinking abilities.
• You should work on your technical abilities as well as your communication, analytical, and decision-making skills.
• A thorough understanding of and familiarity with Google products is essential. You can outperform other candidates if you have a thorough understanding of Google's business and the organization's timeline.
• Refresh your programming and database language knowledge. You should be familiar with both fundamental concepts and advanced problems. Google has high standards for its new hires. You must gain programming experiences, such as with R or Python. Starting with the fundamentals, such as working on the syntax and commands for the specific language, and then progressing to algorithm design and development, is the best approach.
• The Google data scientist interview questions cover topics such as strategy development and management if you are applying for a senior data scientist position.

Wrapping Up!

If you want to work as a data scientist, enrol in Advanced Certification in Data Science & Engineering, to have greater job opportunities as a data scientist in India. 

We've trained thousands of coding engineers, software developers, and data scientists to land dream jobs at companies like Google, Facebook, Amazon, Apple, Microsoft, and Netflix.