American Express Interview Questions and Answers for Freshers

Q1. Everything about Agile methodology - which method do you use, what is sprint velocity, how do you push it in the team, conflict resolution etc. Every question was theoretical - they didnt even ask about my...read more
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Q1. Another round of basic scenario based questions.
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There were three coding questions.

Q1. Could you provide a thorough explanation of the project?
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Q2. OOps Concepts and question from the technical subjects
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Q3. Why Spring Boot
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Q4. JWT Authentication
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Q5. Docker and Kubernetes
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Q1. Work experience and relevance of your resume for Amex
Ans. 
My work experience includes roles in financial services and consulting, providing me with relevant skills for Amex.
• I have worked in financial services for 5+ years, including roles at a major bank and a fintech startup.

• I have experience in consulting, where I worked on projects related to financial analysis and strategy development.

• My resume highlights my expertise in financial modeling, data analysis, and client relat...read more
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Q2. Why change to Amex? What attracted you the most about Amex?
Ans. 
I changed to Amex for its reputation for innovation, strong company culture, and opportunities for growth.
• Reputation for innovation in the financial industry

• Strong company culture focused on employee development and diversity

• Opportunities for career growth and advancement within the company
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Q3. Technology questions such as how API works and your experience in working with data?
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Q4. How you used data management and analytics in your last role?
Ans. 
I utilized data management and analytics to track project progress, identify trends, and make data-driven decisions.
• Implemented data management systems to organize and store project data efficiently

• Utilized analytics tools to analyze project performance and identify areas for improvement

• Generated reports and dashboards to track key metrics and communicate findings to stakeholders

• Used data insights to make informed deci...read more
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Q5. How you can make business decisions from data in your last role?
Ans. 
I used data analysis tools to identify trends, patterns, and correlations to inform strategic business decisions.
• Utilized data visualization tools to present key findings to stakeholders

• Conducted regression analysis to predict future outcomes based on historical data

• Collaborated with cross-functional teams to gather and analyze data from multiple sources
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Q6. How you solved any disagreement with your boss in last role?
Ans. 
I always approach disagreements with a focus on finding common ground and maintaining open communication.
• Listen actively to understand the boss's perspective

• Express my own perspective calmly and respectfully

• Seek a compromise or solution that benefits both parties

• Follow up to ensure the issue is fully resolved
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Q7. How will you approach different teams with requirements as a product manager?
Ans. 
I will approach different teams with requirements by understanding their unique needs, building relationships, and communicating effectively.
• Understand the goals and priorities of each team to tailor requirements accordingly

• Build relationships with key stakeholders to gain buy-in and support

• Communicate clearly and regularly to ensure alignment and address any concerns

• Collaborate with cross-functional teams to ensure al...read more
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Q1. Logical Questions - Check out Geeks for Geeks Puzzles and memorise them all or atleast understand logic for each
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Q2. 3 ants around a triangle problem
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Q3. Find top 3 horses from 25 horses set
Ans. 
To find the top 3 horses from a set of 25 horses, we can sort them based on their performance or rankings.
• Sort the horses based on their performance or rankings

• Select the top 3 horses from the sorted list

• Consider factors like speed, endurance, and previous race results
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Q4. How will you approach conflicts at workplace?
Ans. 
I approach conflicts at workplace by actively listening, understanding all perspectives, and finding a mutually beneficial solution.
• Actively listen to all parties involved in the conflict

• Seek to understand the root cause of the conflict

• Encourage open communication and dialogue

• Find a mutually beneficial solution that addresses the concerns of all parties

• Mediate if necessary to facilitate resolution
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Q1. Behavioural questions
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Q2. How will you manage work life balance?
Ans. 
I prioritize tasks, set boundaries, delegate when necessary, and make time for self-care.
• Prioritize tasks based on deadlines and importance

• Set boundaries by establishing work hours and sticking to them

• Delegate tasks to team members when overwhelmed

• Schedule time for self-care activities like exercise, hobbies, and relaxation

• Communicate with supervisors and colleagues about workload and availability
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Q3. What are the 3 pillars of data management?
Ans. 
The 3 pillars of data management are data quality, data governance, and data security.
• Data quality ensures that data is accurate, complete, and reliable.

• Data governance involves establishing policies and procedures for managing data assets.

• Data security focuses on protecting data from unauthorized access or breaches.
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Q4. How will you solve disputes and disagreements with your manager?
Ans. 
I will approach disputes with my manager by actively listening, seeking common ground, and proposing solutions collaboratively.
• Actively listen to my manager's perspective and concerns

• Seek common ground and areas of agreement

• Propose solutions collaboratively, considering both perspectives

• Maintain professionalism and respect throughout the discussion

• Seek feedback and learn from the experience to prevent future conflicts
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Q1. What is regression
Ans. 
Regression is a statistical technique used to understand the relationship between variables and make predictions based on that relationship.
• Regression helps in identifying the strength and direction of the relationship between variables.

• It is used to predict the value of a dependent variable based on one or more independent variables.

• Common types of regression include linear regression, logistic regression, and polynom...read more
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Q2. What is curse of dimensionality
Ans. 
Curse of dimensionality refers to the issues that arise when working with high-dimensional data, leading to increased computational complexity and sparsity of data points.
• High-dimensional data requires exponentially more data points to maintain the same level of data density.

• Distance between data points becomes less meaningful as dimensions increase, making it harder to interpret relationships.

• Increased computational c...read more
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