If you aspire to work as a data scientist at Amazon, preparing for Amazon data scientist interview questions will help you crack the rigorous Amazon interview process.
Unlike many other tech companies, Amazon's interview process is unique. They take a candidate-first approach, asking pertinent questions and assisting with necessary resources. As a result, preparing for this interview can be challenging. We have compiled a list of frequently asked Amazon data scientist interview questions to help you with your prep.
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We’ll cover the following topics in this article:
Here are a few basic Amazon interview questions for data scientists that beginners and freshers will find helpful:
Data Science is a mix of various tools, algorithms, and Machine Learning principles. The main goal is to discover hidden patterns from the raw data.
The four types of selection bias are:
This is used to summarize all the numeric data in the data frame. For instance: the describe() function can summarize all data values. columnname.describe() will show the following values of all the numeric data in the column-
R is used in data visualization because it has inbuilt functions and libraries. These libraries have ggplot2, leaflet, and lattice. R also helps in exploratory data analysis along with feature engineering.
A typical Amazon data scientist interview also contains the following Machine Learning interview questions:
Machine Learning is the study and construction of algorithms. It is closely related to computational statistics. It is used for devising complex models and algorithms that lend to a commercial prediction known as predictive analysis.
This algorithm is based on the Bayes theorem. It describes the probability of an event based on the prior knowledge of conditions related to that event.
Pruning is a technique in Machine Learning and search algorithms that reduce the size of decision trees. It removes sections of the tree that provide little power to classify instances. Thus, the removal of sub-nodes of a decision node is called pruning.
This is a statistical technique where the score of Y is predicted from the second variable, X. Here, X is the predictable variable, and Y is the criterion variable.
Drawbacks of the linear model are-
Recommended Reading: Microsoft Data Science Interview Questions
Scroll down to find Amazon data scientist interview questions related to Deep Learning:
Machine Learning in computer science enables the computer to learn without explicit programming. It can be categorized into the following categories:
Deep Learning employs a complex set of algorithms modeled after the human brain. This allows unstructured data such as documents, images, and text to be processed.
Deep Learning has existed for a long term; however, the breakthroughs using this technique came recently. This is because:
This method teaches what to do and how to map situations to actions. Its purpose is to increase the numerical reward signal. Interestingly, it is inspired by the learning process of human beings as it is also based on the reward-penalty model.
Like biological neural networks, Artificial Neural Networks work on the same principles. It consists of inputs that get processed.
The Cost Function is also referred to as "loss" or "error." It is a measure to check how good the model's performance is. It's used to compute the error of the output layer during backpropagation.
For more data science interview questions, read this article.
If you are an aspiring software developer or a tech lead, these questions can help you ace your Amazon tech interview. So, don’t delay your tech interview prep and practice these Amazon data scientist interview questions. Check out these sample questions for quick coding interview prep.
Here are a few commonly asked Amazon data scientist interview coding questions:
Also, read Python Data Science Interview Questions to learn about the common Python-based interview questions.
Getting a job at Amazon can be a fantastic move for your career. So, start preparing for the Amazon data scientist interview questions, and you'll be able to land that dream job you've always wanted.
Q1. How to prepare for Amazon data scientist interview questions?
Some effective tips from the experts on Amazon data scientist interview questions are: be prepared for interpersonal and behavioral questions, use the STAR method while responding, answer in detail, do not hesitate and limit your skills or experiences, it is okay to share failures, have a clear idea of why you want to work at Amazon, ask questions to the interviewer, study Amazon’s leadership principles, and research on Amazon’s work culture.
Q2. What are the different stages of the data scientist interview at Amazon?
The Amazon data scientist interview process generally has three stages- Initial Screening, Technical Screening, and On-site Round.
Q3. How long is the interview process at Amazon for a data scientist?
The initial screening process is for half an hour. And the technical round can take up to an hour to complete. At the same time, the on-site interview takes 6 hours to complete.
Q3. Is the data scientist job at Amazon a good career?
Amazon is a top-tier technology company that many people want to work for. Working as a data scientist at Amazon will expose you to a wide range of perks, experiences, and benefits.
Q4. How much does a data scientist earn in the US?
A data scientist earns an average salary of $109,666 per year in the US.
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