Does Google hire a data scientist

The ultimate guide to becoming a data scientist at Google

Becoming a data scientist at Google is not a cakewalk. The job requirements of a data scientist at Google include the following:

• Minimum eligibility criteria of a master’s or Ph.D. degree.
• Two years of work experience.
• Knowledge of statistical software and data analysis field.

If you wish to become a data scientist at Google, you would need to acquire the right skills to stand out. Google is a prestigious employer with a high reputation in the market for its excellent work environment and lucrative salaries. As a result, passionate, motivated, curious, and skilled people are actively recruited by this company. In addition, there are many more tangible benefits of becoming a part of Google’s workplace culture. For example, the average annual salary of a data scientist at Google will be higher than any other company. As per Payscale reports, the average annual salary of a Google data scientist is around $133122. 

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What does Google look for in a data scientist applicant?

Google has a set of basic traits and skill sets that they look for in their employees. There is a list of hard and soft skills that Google looks for in their data scientist employees, such as the following.

Hard skills

A minimum eligibility criterion for becoming a data scientist at Google is a master’s degree in computer science, statistics, or any other science stream. Most job listings on Google prefer Ph.D. and master’s degrees with relevant job experience. Therefore, make sure that your portfolio resume contains relevant details about all the experience from educational qualifications and projects that you have done. In addition, data scientists at Google should be proficient in statistical languages such as Python and R and database languages such as SQL.

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Soft skills

You need to demonstrate a wide range of soft skills at Google. Some of the typical soft skills that Google expects from their data scientist employees are interdisciplinary communication and creative thinking. Many data scientist job listings at Google require professionals to work in close collaboration with other groups, such as product engineering and finance. Strong communication skills and creative thinking will help you deliver actionable and impactful outcomes in this company. 

The hiring process of data scientists at Google

Google is evolving faster and has employed around 114000 individuals since 2019. This company is a top performer in business and technology, hiring highly talented and skilled candidates. Google comes with a multi-step end unique hiring process for each candidate. It starts with a response to a job posting or the initial conversation with a Google recruiter and is followed by an interview process and a group decision-making round. The hiring process for data scientists at Google can be deliberate and slow. They can also hold technical interview rounds to test the abilities and skills of the candidates. Google prefers to ask high-level questions related to programming, computer science, and coding to test a candidate’s skill sets required to perform a data science job. The hiring process for data scientists at Google is unique as the company prefers to hire highly skilled and versatile candidates who can switch from one role to another in their technical field. 

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How to crack a data science interview at Google?

You need to demonstrate your practical and technical skills and personal attributes in Google’s data scientist interview process. Following is how you can ace your data science interview at Google

Showcasing your practical skills

The first and foremost step before applying for a data scientist job role at Google is to hone your practical skills and enroll in professional courses. Here you will get the assistance of industry experts who will help you to go through specific examples and learn how to answer interview questions. It is essential to boost your confidence, and no matter how perfectly well you are at your technical skills, Google will try to hold interviews to see how candidates react under pressure. Following are the critical areas in which you should brush up your knowledge and polish your skills to answer all the Google interview questions confidently

• Coding:

Aspirants willing to become a part of the data science team at Google should go through coding questions. Recruiters at Google will ask data manipulation questions requiring coding to identify insights out of data. 

• Algorithms:

Candidates would be required to solve mathematical problems using programming languages at Google data scientist interviews. Before applying for a data scientist job role at Google, make sure to hone your knowledge in machine learning algorithms and programming languages such as Python and R.

• Statistics:

Recruiters at Google will test your foundational knowledge and statistical theories and your knowledge about associated principles that you must use in the data science process. 

• Modeling:

Google data scientist interview includes questions about statistical modeling and machine learning. Data science applicants must apply their knowledge in using statistical assumptions and mathematical models for generating sample data and making accurate predictions.

• Business Case:

Data science interviews at Google will include questions related to business case studies and other generic business questions to check your data science skills. Google may also ask their data science job applicants to evaluate the performance of their products or services through data.

• Technical:

If you’re applying for a data scientist role at Google, then make sure to acquire knowledge about data science technical fundamentals and concepts. In addition, candidates would be asked to showcase their technical knowledge of data science tools they would have to use at Google to accomplish their tasks.