The Google Data Scientist Interview
Google is an American technology giant that specializes in Internet-related services and products including online advertising, search engines, cloud computing, software, and hardware. The company was founded in 1998 and headquartered in Mountain View California.
With its rapid growth since incorporation in 2002, Google has developed a wide range of products, acquired a long list of companies, and entered into mainstream culture through its dominance in search . Now Google has branched into tons of products and services such as office suite apps, email clients, cloud computing, video chat, android, and tons more.
With the plethora of products and services offered by Google and the staggering number of users, one might ask just how much data does Google handle? Based on 2019 statistics , Google processes over 40,000 search queries every second on average, which translates to over 3.5 billion searches per day and 1.2 trillion searches per year worldwide. To Google, this presents endless opportunity to help its customer grow and scale, and to data scientists this present a treasure trove of information for analysis and interpretation to help identify opportunities for Google and its clients, and shape Google’s business and technical strategies.
If you’re interested in what’s asked on the interview, check out the list of Google data science interview questions .
The Data Science Role at Google
Data scientists at Google work across a wide facet of teams, products, and features, from enhancing advertising efficacy to network infrastructure optimization.
The Google data science role is primarily an analytics role that is focused on metrics and experimentation . This is distinctly different from the machine learning and product analyst roles that also exist at Google that focus more on the engineering and product side respectively. The data science role at Google used to be called a quantitative analyst before switching to data science to attract more talent.
Google usually only hires experienced individuals with at least two to three years of industry experience in analytics or related fields. Google does have programs for internships and university graduates in data science, and specifically has more advanced roles for new PhD graduates.
Other relevant qualifications include:
Masters or PhD in Statistics, Computer Science, Bioinformatics, Computational Biology, Engineering, Physics, Applied Mathematics, Economics, Operations Research or related quantitative discipline, or equivalent practical experience.
Advanced experience in statistical software (e.g MATLAB, Panda, Colab, S-Plus, SAS, etc.), programming language like Python, R, C++, and/or Java, and advanced experience in database language (e.g SQL) and management systems.
Experience with big data and cloud platforms to deploy large-scale...