American Express Interview Experience | Analyst Intern

Selection Process and Rounds 

1. CV shortlist  
2. Online Test 
3. Interview (3 Rounds) 

The 1st round was an OT round and was in 2 parts. In the first part, there were 3 sections among which aptitude section was compulsory (around 30 mins.) and Machine Learning or Business Case Study was kept optional (around 10 – 20 mins). I would recommend attending both the optional sections. The second part of the OT was a psychometric test (around 25-30 mins). Psychometric Tests are behavioural test in which you might get the same question at different instances during the test with a different intent. 

I had 3 PI rounds and all were Tech cum HR. Mostly the questions were puzzles, case studies and related to the projects I had mentioned in my CV like the application of projects in their company. (P.S. In 2 of the 3 PI rounds, they asked about the project I had done at ISI Kolkata in my previous summer internship.) 

Interview Rounds: 



Round 1: 

Questions were from basic ML topics, clustering techniques, dimensional reductions etc. Ex. I was given a question of the debit card data usage in a hotel where a few features like the location of the hotel, transaction amount and transaction date etc. made a 1000 dimensional vector. I was asked to reduce the dimensions to the least possible value without much change in the accuracy. 

Round 2: 

The interviewer asked about the most difficult problem in my previous round and what I thought my answer to it was. Then she picked up a project form my CV and asked a few questions related to the algorithms used, approach etc. I was asked to generate 100 numbers from 1 to 100 randomly without any code, without asking anyone else. A real-life scenario where any number I pick has to lie between 1 to 100. 

Round 3: 

Other than my project discussions, a few puzzles were asked. 

a. The exact question and answer http://www.crazyforcode.com/100-lockerdoors-puzzle/ or https://www.geeksforgeeks.org/puzzle-16-100-doors/

b. similar to https://www.geeksforgeeks.org/puzzle-9-find-the-fastest-3-horses/ 



Overall HR questions: Other than the normal HR questions which included introducing oneself with your strength and weakness, hobbies etc., a few questions were related to the company as well – like how they earn, their business model, related to different teams at AmEx etc. 

  

Two of three Technical cum HR rounds were purely based on my previous Internship project. They drilled every possible detail about the project, the application of this project in different fields, my approaches, my shortcomings, difficulties faced during the project etc. The interviewer also asked about the used cases of some algorithms, the reason why I chose a particular approach over any other methods etc. 

  
 

Preparation Strategy & Materials:

1. Puzzles from https://www.geeksforgeeks.org/puzzles/ and http://www.crazyforcode.com/brain-teasers/ 

2. Practice a good number of case studies and aptitude problems. 

3. Since the profile was analyst, they may ask ML related topics. Go through some good Medium articles – https://medium.com/ 

4. Though I wasn’t asked any coding question, there were a few who were asked basic programming questions. So, better if you have hands-on programming knowledge in C/C++ other than python. 

  

SUGGESTIONS: 

1. Aptitude is the basic round for almost every company. Keeping this in mind, learn different tricks and techniques from youtube and solve problems. Helps you in the PIs as well. 

2. Case studies revolve around your knowledge on the given field which may include socio-economic aspect as well. Keeping this in mind, interact and get as many insights from the interviewer as possible. Sometimes, they can ask about guestimations as well (were asked to a few other candidates). 

3. If you have done any past internships (not for the sake of certificate) and projects, kindly know every minute of it like your algorithms, your approach, the reason why you went for a particular approach, the shortcomings, larger use cases of the algorithms etc. 

4. Know about the company well. Research about the company, about the roles they are offering etc. and make the conversation interactive when they ask about you or about their company. 

5. Be confident. There may be instances where things might go wrong, but take a deep breath, calm down, think and respond well.
 


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