American Express Analyst – Harshita Gupta

American Express Corporate Experience by Harshita Gupta, Analyst at Data Analytics team. A compilation of her learnings and suggestions for the applicants.

Corporate Experience as Analyst at American Express
American Express Corporate Experience

Hi everyone, hope you’re all doing good.

I am a 2020 batch postgraduate from the Department of Statistics, University of Delhi. I secured an offer with American Express from my campus and I am currently working as an Analyst. My location is Gurugram and I am working in Data Analytics team. 

At American Express, my current role involves the development and execution of analytical solutions to drive profitable marketing, customer/prospect targeting, and credit business actions. The day-to-day work includes analyzing a large amount of data to derive business insights and create innovative solutions. Developing newer and better approaches to solve business problems includes a lot of data preparation, data exploration, and understanding of machine learning solutions. In addition, my role also includes presenting all analysis and business insights to senior leadership in a simple and concluding way.

The tools that I use on regular basis are Hive, Python, and Pyspark.

Quick Tips for Fresher’s who are looking into Business Analytics Role:
  1. Keep your Statistical/ Mathematical basics strong. In an Analytical role, you might not be directly working with models. But you will be, at times, leveraging modeling solutions that will require your understanding of how they have been developed. Your academic basics will also help you develop ideas and explain the data more effectively.
  2. Learn SQL from any source. Learning SQL will not take much time, and it will surely help you build a career in Data Science or Analytics. Most of the roles involve data preparation activities which require a good command of SQL.
  3. Spend sufficient time learning MS-Excel, it will make your life easy at corporate. The storytelling and analyzing data is certainly very helpful and quick with pivot tables, charts, and various functions of MS-Excel.
  4. Effective Communication is very important as you will be partnering with multiple teams on a project within your company.
Some Interview Preparation Sources/ tips:
  1. Utilize online courses from Coursera, Datacamp, Udemy, Analytics Vidhya, Youtube to learn any Data Science or Analytical course on R, Python, Excel, SQL.
  2. Read online blogs, like Analytics Vidhya, Medium, TowardsDataScience, ListenData, etc, to study or clear your doubts on any topic.
  3. Practice working on large datasets from Kaggle. Consequently, this will help in improving coding as well.
  4. Be crisp and clear on definitions of any terminology asked in the interview (like p-value, correlation, regression, multicollinearity, etc). Try to explain the same using a real-life example after a definition.
  5. Don’t ruin your interview if you are unable to answer some questions. Feel confident to say NO on the topics you are not aware of.
  6. Communicate with the Interviewer while you are solving any puzzle, guesstimate, or any business case study. This will help you deliver your approach effectively and discussion will be fruitful.
  7. Stay confident in your preparations, concepts, and approach during Interviews as communicating with confidence plays a key role in selections. Never let your confidence go down due to some unanswered questions. Focus on answering the rest of the interview nicely.

I hope this helps all the students. All the best to everyone in the process. Something good is coming your way. 🙂


Harshita Gupta

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