Being an easily recognisable tech mammoth, Google has transformed our lives with its search engine service and all the other subsequent tools provided at our disposal. Google’s best asset is data.
It collects all its data from numerous sources and uses it to enhance customer experience. For example – Google Maps uses data to predict traffic jams, Google search engine uses interaction data to generate relevant search results, and more.
Therefore the role of Data Scientists at Google is highly valued. It is said that getting a Data Scientist role at Google is highly competitive and if one is lucky enough, they might land the job & become a “Googler”
Google has been very thorough with their hiring process which helps them comb through the list of candidates and select the best of the best Data Scientists.
So what does Google seek in a Data Scientist?
A Data Scientist candidate is expected to be good at Critical thinking, Coding and Communication. Since most of the work is mechanical, the core knowledge of Data Science and how it is implemented is where one shines.
There are many who have battled their way through and experienced the Google Data Scientist interview process. Therefore, from all the experience shared by interviewees you will find information on the what’s and how’s of the interview process for a Data Scientist role at Google.
What does a Data analyst do at Google?
- They evaluate and improve the company’s products and services.
- Use data analysis at every stage of the product development and deployment process.
- Implement specialised background knowledge and skills to different facets of Data Science.
If these seem intriguing, then you are on the right path.
Now let’s dive into the interview process for the role of a Data Scientist at Google.
As per the collective experience, Google requires all candidates to fill up an application online, before they go through the phone interview, technical video conference interview and lastly an in person interview in one of the Google offices.
How do I prepare for Google Data Science interview?
Interview rounds for a Google Data Scientist role
Stage 1- Telephonic interview:
The Google Data Scientist interview begins with an interview over the phone, where the recruiter asks the candidate about their background, total experience and all the basic ice breaker questions that help them understand why you as a candidate want to work with them.
This stage of interview is a common practice and is shared by many interviewers including other tech giants, such as Apple, Amazon and Facebook.
Stage 2- Technical video conference interview:
This stage, as the name suggests, is an interview over a video conference when the recruiter gets a better understanding of where one stands as a potential candidate. The technical capabilities of each candidate are observed via the Q&A round.
Questions about A/B testing, statistics, experimental design are asked and even a small coding assignment can be given to candidates on the spot. This is where your background knowledge of SQL and Python skills will come in handy and help you set apart and secure a spot.
Few questions that have been asked before include: “Write a function to reverse a string” and “For a sample size of N, the margin of error is 3. How many more samples do we need for the margin to hit 0.3?”.
Stage 3- On-site interview:
Once candidates have cleared the previous rounds, they are called for a face to face interview with five different interviewers. These interviewers are from different departments, ranging from Data Scientists, Product Managers and Business Executives.
This round of interviews will also include technical and situational questions but each candidate will be mostly assessed for their all rounding leadership qualities, culture fit and ambiguity at the workplace.
Pro Tip: Google tends to ask questions about its products and services. So, it is important to acquaint yourself with all of Google’s products. The recruiters might want to look into constructive feedback and assess one accordingly.
Something to note is that Google has had a history of asking similar questions in most of their interview stages. Many candidates who have gone through such interviews share the same experience. In order to help you gain insight, we have compiled a list of such questions.
It is a good idea to go through and practice these, since being prepared will surely increase your chances of getting through
20 Most Common Questions Asked By Google
Linear Regression questions
- Derive the Gaussian discrimination method under three different cases. Robust linear regression. Bayesian probability calculation. Random Markov Field. RNN.
- Why use feature selection? If two predictors are highly correlated, what is the effect on the coefficients in the logistic regression? What are the confidence intervals of the coefficients?
- Explain LASSO RIDGE, Research Paper, Optimization etc.
- What is the assumption of error in linear regression?
Python questions
- How would you find the top 5 highest-selling items from a list of order histories?
- Write a code to generate random normal distribution and plot it.
- Write code to generate iid draws from distribution X when we only have access to a random number generator.
- Write a function to generate N sample from normal distribution and plot the histogram.
Clustering questions
- K- mean and Gaussian mixture model: what is the difference between K-mean and EM?
- How to decide k in kmeans?
- When using a Gaussian mixture model, how do you know it is applicable?. If the labels are known in the clustering project, how to evaluate the performance of the model?
Other Miscellaneous Questions
- Explain a probability distribution that is not normal and how to apply that.
- There were essentially typical probability questions about confidence intervals, sample size, and hypothesis testing, MC simulations.
So this is how the interview for a Data Scientist role at Google looks like, and we hope this helps you nail your interview at Google.
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