American Express Data Analyst Interview Questions and Answers

Three sections of apti, ML and Case study

Q1. Factors to account for ATM placements in city?
Ans. 
Factors such as foot traffic, proximity to banks, crime rates, and demographics should be considered for ATM placements in a city.
• Foot traffic in the area

• Proximity to banks or financial institutions

• Crime rates in the neighborhood

• Demographics of the area (income levels, age groups)

• Accessibility and visibility of the location

• Local regulations and zoning laws

• Availability of power and network connections

• Competition from ot...read more
Answered by AI
Add your answer

Q1. How would you decide if a person can be a customer of a private jet company
Ans. 
To determine if a person can be a customer of a private jet company, factors such as income level, travel frequency, and location must be considered.
• Consider the individual's income level to determine if they can afford private jet services

• Evaluate the person's travel frequency to see if they would benefit from the convenience of private jet travel

• Take into account the person's location and travel destinations to asses...read more
Answered by AI
Add your answer

Three Data model questions will be given to solve within 24 hours.

Q1. Q1. Case study for Number of Green T-shirts sold in US?
Ans. 
A case study on the number of green T-shirts sold in the US.
• Identify the target audience for green T-shirts

• Analyze the market demand for green T-shirts

• Study the sales data of green T-shirts in the US

• Identify the popular brands and styles of green T-shirts

• Analyze the impact of seasonality on sales

• Consider the pricing strategy of green T-shirts

• Identify potential marketing opportunities to increase sales
Answered by AI
Add your answer
Q2. Q2. SQL joins and Python simple questions
Add your answer

You are building a model to predict if an order will be returned for a furniture ecommerce site.
1. steps to be followed.
2. What all features would you select based on your business sense.

Q1. Why this job interests you?
Add your answer
Q2. Tell us your past experience
Add your answer

Q1. Explain why and when Analysis of Variance (ANOVA) is used. {Question from CV, since I had mentioned the use of it before}
Ans. 
ANOVA is used to compare means across multiple groups to determine if at least one group differs significantly.
• ANOVA is used when comparing three or more groups to see if their means are statistically different.

• Example: Testing the effectiveness of three different diets on weight loss.

• It helps in understanding the impact of categorical independent variables on a continuous dependent variable.

• Example: Analyzing test sco...read more
Answered by AI
Add your answer
Q2. ,You want to create an index that comprises of a bunch of components. How would you choose to aggregate all the individual components? Is it context specific?
Ans. 
Choosing an aggregation method for an index depends on the components and their context, ensuring relevance and accuracy.
• Identify the components: Understand what individual metrics or data points will be included in the index.

• Determine the aggregation method: Common methods include sum, average, weighted average, or geometric mean.

• Consider the context: The importance of each component may vary based on the specific app...read more
Answered by AI
View 1 more answer

Question:
Suppose you are trying to detect if a particular credit card transaction is fraudulent or not. The credit score of the individual to which the card belongs to had a very healthy credit score. All bills were paid in time and average transaction amount was not that high ($800). The individual had not been out of the country in the last couple of decades. Here is a list of transactions:

1) Gold jwelleries worth $5000
2) Groceries worth $35
3) Second hand car worth $8,000
4) Burgers worth $10

Which transaction looks fraudulent to you?
There is no specific answer. They just want to see how you think through the problem. One can potentially make use of data in order to deal with this problem. From that, one can estimate the probability of each of these transactions being fraudulent. Econometrically, one can develop a potential binary logit model. That would involve identifying certain features that belong to individuals like the one considered above and use these features to come up with an estimate of the probability of the transaction being a fraud.
Not just that, this also needs to include not individual specific features but external features as well. For example, the first transaction might not be as fraudulent as it looks like, because in heavily regulated markets, the risk associated with reselling the gold or exchanging it for money might be high enough to disincentivise the fraudster from buying gold. Thus regulation might also be a valid feature, and different from features describing an individuals characteristics.
Ofcourse problems of overfitting would arise ifan excessive number of features are used. Various means of finding the optimal Degrees of Freedom can be employed.
Obviously one can do better with more complicated decisioning algorihms that involve machine learning models as well.
Eventually one needs to estimate at what threshold of probability will the trasaction be declared fraudulent.

Q1. Sort an array without using the inbuild function.
Add your answer

Mettle test on quant and machine learning

Q1. How will you handle an office emergency
Ans. 
In an office emergency, I prioritize safety, assess the situation, and follow established protocols to ensure everyone's well-being.
• Stay calm and assess the situation quickly to determine the nature of the emergency.

• Ensure the safety of myself and others by following emergency protocols, such as evacuating if necessary.

• Communicate clearly with colleagues about the emergency and any actions they should take.

• If applicabl...read more
Answered by AI
Add your answer
Q2. What are your strengths
Add your answer