Amazon data analyst interview experience

Amazon Data Analyst Interview Experience

After two great years at the Nordstrom Data Lab, I was offered a position in the Amazon Web Services S3 department. I was excited for the new chapter in my life that was about to begin, and relieved that the time-consuming and grueling interview process was finally over. Interviews typically include one of three preliminary screenings, as well as a full-day on-site interview. These interviews are stressful because you don't know what you'll be asked, and you're usually expected to show off your intelligence, which is something a data scientist wouldn't normally do (at least not out of context and just from memory on the phone). intelligence).

You need time

If you are thinking about changing jobs (or entering this industry), the best advice I can give is to start preparing now. You need to give yourself plenty of time and avoid cramming mode. Take the time to make sure you can explain the core concepts in your own words. A phone interview question usually goes something like this: "How would you explain to an engineer what a p-value is?" Let's say you want to explain it to an engineer who is not a statistics major and doesn't use technical jargon. It goes without saying that you don't want to have to explain these basic concepts for the first time in such a setting. Also, don’t underestimate the impact of stress on your memory, even when you’re recalling something you thought you knew well. If you are new to the industry, you may need to give yourself more time to prepare for concepts you are unfamiliar with.

I also recommend spending more time preparing personal information, namely your resume and cover letter. There are two views on this issue, one thinks it is important and the other thinks it is not important. Do interviewers really look at this information? It’s hard to answer in general terms, but I went on a ton of interviews when I worked at Nordstrom, and personally, I take this information very seriously. Spelling errors will not be tolerated. A self-proclaimed cover letter is not a good sign. A bad profile indicates a lack of interest in the position (or a lack of respect for the reader), and keyword stuffing signals the interviewer to ask where and when the applicant did this. In the broader technology world, there's a tendency to think that it's what's on GitHub that matters. But most companies, especially larger ones, won't look at your GitHub. They look at resumes and cover letters (this may be surprising, but tech is not a meritocracy). Ultimately these documents will reflect how you present yourself professionally, so they do matter, even if you didn't think so before.

Practice brings true knowledge

I recommend doing more practice and analyzing your own weaknesses. Many people mistakenly believe that reading books repeatedly is the most effective way to learn, but this is not an effective way to solve probability problems and logic puzzles on the spot (before you start studying, the book "Make it Stick" is highly recommended). By focusing on real-world problem solving, you'll immediately identify your weaknesses and prioritize your learning. Spending time on something you already know is a form of procrastination, especially when you're already busy. Additionally, this is a technical field and you should be prepared to answer questions at a technical level. If you can, I recommend standing in front of a whiteboard and answering practical questions to get yourself comfortable with writing and speaking as you go. You can find a lot of relevant advice and interview questions on Quora.

Learn as much as possible about the future position

Do you know what an informational interview is? Before my friend used this method, I didn’t know what it was! Sometimes The interview process is moving forward, but you don't know if you want the job. Then you can ask the person to slow down and do an informational interview to determine if this is the job you really want. You can also spend time "peeping" at the company and the interviewer. For example, for my on-site interview at Amazon, I spent time checking each interviewer and their background on Linkedin. This will help you guess the questions they will ask. Oh, this person is an engineer, so she may not ask you about statistics, but she may ask about expansion methods. Wait she's a senior management engineer, maybe she'll want to know about my leadership and interpersonal skills. Ellen Chisa has lots of advice on interview no-nos.

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You can expect to be asked about: statistics, machine learning, prediction, algorithms, everything a CS undergrad should know, and Scalability and performance related to all areas above. Oh, and you'll also want to prepare to program in a language of your choice. A piece of cake, right?!

Books

Get an introductory book on probability theory, it doesn’t matter which one it is. I used the textbook written by Ross, which is a typical undergraduate probability theory textbook. If you have this copy, I recommend taking the self-test questions on chapters 1-5 to decide whether to spend more time on it. Combinatorial mathematics and basic probability questions are essential for phone interviews, so make sure you master them. I also used the textbook written by Casella and Berger to review expectations and variances. This book can be said to be the bible of statisticians. Generally speaking, most interviews are easier than the textbook.

For computer-related content, I generally refer to three books: "Programming Interviews Exposed", "Cracking the Coding Interview" and "Programming Pearls". The first volume is the most comprehensive of the three. If you only have time to read one book, read this one. The second one is concise and specific, targeting interviews at large companies like Amazon, Google and Facebook, but is not widely applicable. The version I use also has some annoying illustrations that teach you to make sure you're "a buddy the interviewer is willing to ask you to drink." This book was so annoying that I finally gave up reading it (I was expecting to get more valuable content). The third book is not about interviews. It is a collection of mental interpretations of computational problems and solutions. This book is not only suitable for learning, but also for understanding the calculation process. It would be a pleasure to read this book if you have time.

Yes, it’s Coursera. If you have thrown away your old textbooks and don’t want to buy any books, the materials on Cousera can satisfy you. I highly, highly recommend the Johns Hopkins Biostatistics Bootcamp. This is an effective review of a first-year undergraduate statistics course. Don’t spend too much time watching course videos. Test yourself with test questions and assignments, then watch videos on weak areas. Also check out data science specialization courses. The class above is organized by the same teachers, and the content includes exploratory data statistics and R programming. Ng Enda's machine learning must be learned and enjoyed. He is good at explaining the motivations behind his methods and spends a lot of time training his intuition during the course. Intuition is especially helpful in phone interviews, where you may not want to stress technical details but still need to demonstrate familiarity with the field. Since my goal at that time was Amazon, I also benefited from the cloud computing specialization course. I'm moving from retail technology to cloud computing and want to better understand the problems I'll be facing. In this case, I only watched the course videos to learn the terminology of the field without delving into the technical details. I am always searching for good Coursera courses. If you have any recommended courses, please leave me a message!

Coursera’s course start and end time system irritates me. Recently I discovered that many courses allow you to browse previously archived materials without having to wait for a new class to start. This is an important change for me, go and try it!

The above is what I call dry information. But I also want to talk about some truisms.

First, stay calm! Being too nervous will make you unable to recall some knowledge. This is a problem for me and makes me do some crazy things like write everything down and stick it on the wall, but I don’t recommend this to everyone. My latest crazy trick is to do aerobics a few minutes before a phone interview, making myself sweaty and out of breath. In addition, if you live in the city where the target company is located, make an appointment directly with the interviewer. I'm expressive and can perform better than in a phone interview.

Don’t forget that you are also interviewing the other person. Trust your gut. I once conducted an informational interview with a startup. I felt patronizing and not listening to what I had to say, but I was still interested in the job. I tried to follow up but it took ten thousand appointments each time to get confirmation. It was a terrible experience and if I had trusted my instincts (these people were unreliable) I wouldn't have wasted so much time. No matter how interesting your job is, it's not worth spending eight hours a day with people who don't respect you.

Finally, don’t compare your experience with others, because you may misunderstand or be disappointed. When I was going through interviews, it happened that some colleagues I knew well were also being interviewed. When I compared my experience with others, I felt surprised and angry. To put it simply, a junior male colleague and I interviewed for the same position in the same week. He was interviewed in person by team members, who asked him very basic questions such as the probability of rolling a dice. However, I was interviewed by phone by people from different offices, and the other party asked me an optimal solution problem in game theory. This is hard to accept, and it's hard not to think about it and not get angry. Now I explain this to inexperience in recruiting and immaturity of the company. This company doesn't know how to interview me for the position, and may even hire someone I don't want to work with because of it, and I don't want to work in a place like this.

Ultimately you should be as prepared as possible, but don’t be upset if there are gaps in your knowledge. Believe in yourself and your own impressions. Learn from failed interviews to nail the next one.

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