Google Data Scientist Salary – For Fresher and Experienced

Google Data Scientist Salary

If you are serious about making it as a data scientist, you know that the only way to get there is through hard work and long hours. Unfortunately, that’s not something most of us can do without being able to support ourselves financially. However, there is good news! Just like any other lucrative career path, there are plenty of data science salary opportunities out there. By knowing how much a Google data scientist makes and how much you can make as a data scientist, you can make a more informed decision about whether to pursue that career path.

What is a Data Scientist?

Data scientists are experts at turning data into actionable insights that businesses and customers can both benefit from. They must be able to work with the information in multiple ways, including planning how to deliver results by analyzing it along with management, data engineering, visualization, and more different teams. Data scientists help innovate on behalf of their organization in a variety of fields such as research or marketing. These professionals often provide deep insight when they’re employed by companies.

What are Data Scientist Roles and Responsibilities in Google?

As a Google data scientist, you will be responsible for providing insights across various product areas, such as Search, YouTube, Ads, and Google Cloud products. Since you’ll be working across many different teams, you’ll be responsible for helping to define the data needs and help coordinate the data science process across teams. This often involves working with engineers to drive the design and creation of products, as well as helping to define the best use of data for product managers and other business stakeholders.  Google data scientists are generally responsible for the analysis of data for products such as Search, YouTube, Ads, and Google Cloud products. They are also responsible for building models that help brands and companies understand their audiences and optimise their products. Finally, they also often work with data science teams to provide new insights and solutions to businesses and brands that are looking to improve their marketing and sales efforts.

Key Reasons to Become Google Data Scientist

This is a fantastic job opportunity that can take you to the next level of your career. Not only will you be working closely with some of the most talented people in the industry, but you’ll also be gaining a deep knowledge of the data science and machine learning process. In addition to that, you’ll also get to work with some of the world’s largest brands and help them improve their products and services by taking advantage of all the data Google collects.  The best thing about this job is that it can take you to the top of your field and provide you with a lot of opportunities for salary bonuses and equity. Google is one of the best places to work in the industry and the data scientist’s salary is one of the highest in the industry. This is a great place to work for the long term and will be a great place for you to develop your skills and career.

  • The main thing at google is to not get fixated on algorithms and tools because they’re always changing. They might be the answer today, but tomorrow may have something new that’s better. It doesn’t matter how well you learn an algorithm; it’s more about a “learning mindset.” Question why things are the way they are and find answers to your questions–that is what will set you apart from other learners out there!
  • You could read a textbook and learn theories, but they probably won’t stick with you. If you have a real problem to work on, the pain will make it much more memorable for you.” The advice to get hands-on experience is something that newcomers should listen to.
  • Like most tech companies, Google first evaluates its employees on their problem-solving abilities, leadership skills, and project execution. However, it also prioritises Googleyness: what an employee brings to the company’s culture. Some “Googley” attributes include acting with the customer in mind – especially when it comes to your team – having initiative beyond your core work responsibilities (not just those outlined) and participating in Google events like training or recruiting. One of these is that being a Googler is incredible; people would be hard-pressed to find a better company than this!

Google Data Scientist Salary

According to the indeed the base salary of a Google data scientist is $120,000. This figure can increase depending on the experience and location of hiring. The median salary for data science roles is $120,000, so you can expect to make somewhere around this figure.  The median pay for a data scientist is $120,000, meaning that half of the people in this role will earn less and half will earn more. The mean salary for a data scientist is $135,899, meaning that the majority of data scientists make a salary around this figure. The highest 10% of data scientists earn an average of $206,796. Let’s look into the details:

Google Data Scientist Salary by Experience:

Google Data scientist’s salary of $120,000 is the base salary of data scientists. You can see that the highest 10% of people earn between $170,000 and $300,000 a year. This suggests that the highest-paid data scientist will work on complicated problems and unique streams of data with few constraints. Here is the list of salaries of data scientists by experience:

Years of ExperienceTotalBaseStocks(/yr)Bonus
1-3 Year$200K$130K$40K$30K
3-10 Year$360K$180K$100K$30K
8-10 Year$425K$215K$150K$20K
10-15 Year$600K$250K$200K$50K

Google Data Scientist Salary by Location:

The base salary for a data scientist at Google varies depending on the location of the hiring organization. The higher the location, the higher the salary. The following figures show the median pay for data scientists at Google, as well as other locations. Here is the list of salaries of google data Scientists in different cities in the US:

LocationAverage Salary
San Francisco$220K
San Jose$209K
New York$250K
Mountain View$220K


Google Data Scientist Salary by Skillset:

A Data Scientist at Google is a driver for exciting new products, services, and solutions at Google. Whether it be taking on a novel research project or helping to lead the engineering teams and emerging solutions that are developed at Google, there’s always something new to learn in this role. Answering tough insight-driven questions at Google is a rewarding experience in itself but beyond this, the workday is made more enjoyable by working on interesting problems that shape industries while improving efficiencies or meeting new business targets. Here is the list of salaries by different skill set: 

Python Developer$161,743/yr
Machine Learning Scientist$290,876/yr
Research Scientist$240,764/yr
Data Scientist$250,467/yr
Machine Learning Engineer$230,257/yr
Data Analyst$195,472/yr
Data Engineer I$165,467/yr

Google Data Scientist Salary by Level:

Junior, Mid-level and Senior Well, there aren’t a huge amount of junior-level data scientists in the company.  At the New York and Toronto offices alone, there’s around forty or so of that grade. We have quite a lot of medium-level data scientists too but we’ve also only got a handful of senior-level data scientists. The question is basically – is this the case across Google?

No surprise here. Big tech companies are the biggest employers in Silicon Valley and they pay world-class wages to their employees! We can base our findings on other industries too like finance, healthcare, law, and government. In that case, average salaries for banking and consulting for these roles were found above $125000 back in 2013 (the salary was $169000). Other sectors like law, management consulting, and accounting tend to pay between $125000 and almost $200000 per year.


Benefits at Google

Google has a long list of benefits and perks. One of the things that should be top of the list for any data scientist job is the generous benefits package.  As a Google data scientist, you’ll be covered by the most comprehensive benefits package in the industry. This includes medical, dental, and life insurance coverage as well as parental leave, flexible work policies, and more. Google also offers other benefits such as funding for education, a rewards program for employees, and more.  Google also offers a number of perks for employees, including a lunch program, an on-site gym, and more. This is the chance of a lifetime to work for a company like Google and take advantage of everything Google has to offer employees.

As a data scientist at Google, you’ll have the opportunity to take part in some of the world’s most innovative research. Google is one of the largest search engine firms in the U.S., making searches possible at an affordable price. This means that not only does Google translate search words into data, but studies are performed daily to find and sort out any sense that isn’t yet there as well. These searches include questions questioning whether certain accents should be included in the search and even how to improve mental health through technology. As a data scientist at Google, you’ll become part of something much more than just code deciphering text-based searches. You’ll explore new applications for technology and transform society with discovery after discovery.

How to Crack the Google Data Scientist Interview?

If you want to become a data scientist at Google, you need to put in the hard work and get ready for the interview process. This is not an easy job, and you’ll need to have the right skills and experience to be successful in the role. In order to succeed in the interview process, you need to have a strong understanding of the different Google data science roles, their responsibilities, and why you would be a good fit for the role. You also need to be prepared with questions that will help the interviewer understand your motivation for pursuing a career in data science. The best way to make sure you are ready for the interview process is to practice asking questions and practicing your responses. This will help you get ready for the interview process and make sure you are prepared for the questions that will be asked during an interview for a data scientist position at Google.  Google has recently released an online data science course that you can complete in a few months. This course is designed to help you get started on the right foot and learn the skills you’ll need to become a data scientist.

Read More About: Data Science Interview Questions


If you are looking for a career that will take you to the pinnacle of your field and provide you with immense opportunities for salary and equity, then the Google data science position is for you. Not only will you be working with some of the most talented people in the industry, but you’ll also get to learn a great deal about the data science and machine learning process. In addition to that, you’ll also get to work with some of the world’s largest brands and help them improve their products and services by taking advantage of all the data Google collects. This is a once-in-a-lifetime opportunity, so make sure you make the most of it!


Q.1: Is data science a high-paying job?

Answer: Yes, data scientists are in high demand and earn a lot more than their average counterparts in the field.  They also have great job opportunities competitively with market salary and compensation, ample relocation deals (such as Google’s $170,000 for a data scientist), an equity bonus, a work-life balance, ample travel opportunities, and an inclusive culture. Doubtless, people who pursue careers in this profession will be rewarded with a higher salary.

Q.2: Which degree is the best for a data scientist?

Answer: One of the most popular degrees associated with data science is a computer science degree. But even though you don’t necessarily have to have a college degree in CS, having a basic understanding of computer science would be nice to have. Even those people who have gone on solely to pursue data science education should be able to handle the course.

Additional Resources

Previous Post

Top 10 Applications of Deep Learning You Need to Know

Next Post

The 6 Main Types of Information System

Exit mobile version