American Express Data Scientist Interview Questions + Guide in 2024
Overview
Founded in 1850 as a freight forwarding company in the US, American Express has since evolved into a global services leader. Today, they offer customers access to a wide range of products, insights, and experiences that enhance lives and drive business success.
As a data scientist in American Express, they play a critical role in leveraging data to drive business growth, manage risk, and enhance customer satisfaction.
In this guide, we will walk you through some of the frequently asked American Express data scientist interview questions, along with tips to help you stand out and make a lasting impression to your future employers.
Cultural and Behavioral Questions
This feature is currently experimental, and we’re committed to improving it with your valuable feedback.How would you approach the problem of detecting whether credit card fraud occurred? Walk me through how you would model this problem, considering various statistical techniques and machine learning algorithms.
In addressing the issue of credit card fraud detection, I would first conduct exploratory data analysis (EDA) to understand the features of the dataset. This includes identifying patterns, trends, and anomalies within the data. Next, I would preprocess the data by handling missing values, normalizing features, and encoding categorical variables. After preparing the data, I would consider various modeling techniques such as Random Forests or Gradient Boosting Machines due to their ability to handle imbalanced classes, which is common in fraud detection scenarios. I would also implement cross-validation to ensure the model's robustness. Finally, I would evaluate the model using metrics like precision, recall, and ROC-AUC to ensure high accuracy in detecting fraudulent transactions while minimizing false positives.
Describe a time when you had to coordinate with another team to complete a project. What challenges did you face, and how did you overcome them?
In a previous project, I needed to collaborate with the marketing team to develop a predictive model for customer acquisition. The challenge was aligning our objectives, as their focus was on immediate campaign results while I aimed for long-term predictive accuracy. To overcome this, I organized a series of meetings to clarify our goals and share insights from both sides. By fostering open communication and creating a shared timeline with milestones, we established a collaborative approach. As a result, we successfully launched a campaign that not only met immediate goals but also provided valuable data for future modeling efforts.
Can you describe a challenging data analysis project you worked on and how you navigated the difficulties?
I once worked on a project where I had to analyze customer behavior data to identify factors influencing churn. The challenge was the large volume of unstructured data. To address this, I first utilized natural language processing techniques to convert text data into usable features. I then employed clustering algorithms to segment customers into distinct groups based on behavior. This helped in identifying patterns that indicated potential churn. The analysis led to actionable insights, allowing the team to implement targeted retention strategies, ultimately reducing churn by 15%.
What Is the Interview Process Like for a Data Scientist Role at American Express?
Phone Screening
The process often begins with a phone call with a recruiter who will discuss your background, the role, and your interest in American Express. They may also ask basic questions about your experience, skills, and expectations.
Onsite Interviews (or Virtual Onsite)
This round includes technical, live coding, and/or case study interviews conducted by a team member, typically a senior data scientist. In addition to the technical questions, you might be asked some behavioral interview questions to see culture fit.
Hiring Manager Round
The final interview involves a conversation with the hiring manager or a senior leader. This round focuses on cultural fit, your motivations, and how you align with the company’s values and goals. Expect to be asked technical questions as well.
What Questions Are Asked in an American Express Data Science Interview?
Here are a few questions that get asked in American Express data scientist interviews:
- Why do you want to join American Express?
- What’s a random forest?
- How do you handle and avoid overfitting?
- Based on the customer spending data, how would you determine what our next partner card should be?
- You’re a credit card company with 100K small businesses as potential partners but can only reach out to 1,000. How would you prioritize which businesses to contact?
- Write a SQL query to select the 2nd highest salary in the engineering department.
- What’s the difference between bagging vs boosting?
- If a logistic model is heavily weighted on a variable, and some values in that variable have lost their decimal points (e.g., 100.00 becomes 10000), is the model still valid? Why or why not, and how would you fix it?
- Write a query to show the number of users, number of transactions placed, and total order amount per month in the year 2020.
- Write a SQL query to calculate the total expenditure for each department in 2022.
- Write a Python function
max_profitthat takes a list of stock prices and returns the maximum profit from one buy and one sell. - Your co-worker develops a model that takes in customer inputs and returns if a loan should be given or not. What metrics would you track to measure the success of the new model?
- How would you build a credit card fraud detection model?
- You notice that the credit card payment amount per transaction has decreased. How would you investigate what happened?
- How would you prioritize multiple deadlines?
- How would you resolve a conflict between your colleague?
- Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return
None. - Write a query to get the total three-day rolling average for deposits by day.
- Given two tables:
employeesandprojects, find the sum of the salaries of all the employees who didn’t complete any of their projects. - Given a dataset, how would you analyze the dataset to understand exactly where the revenue loss is occurring?
How to Prepare for a Data Science Interview at American Express?
Here are some tips to help you excel in your upcoming American Express data scientist interview:
Understand the Role and Company
Research about American Express and familiarize yourself with their product, partnerships, and any challenges they face in the finance industry
Brush Up Your Technical Skills
Study key data science concepts like statistics, machine learning algorithms, and data manipulation, with a focus on languages like Python, R, and SQL.
Practice solving case studies
Practice solving data science case studies relevant to American Express’ business problems such as customer segmentation or credit risk assessment.
Showcase Soft Skills
Prepare to articulate your ability to communicate complex technical concepts to non-technical stakeholders, collaborate effectively with cross-functional teams, and solve business challenges efficiently. Practice using the STAR method to structure your responses in behavioral interviews.
Do Mock Interview with Peers
Nothing beats practicing for data scientist interviews with another person to get real-time feedback! Use our P2P Mock Interview Portal and AI Interviewer to conduct mock interviews with friends or fellow candidates. Focus on clear and concise communication to receive constructive feedback on your responses and refine them for your upcoming American Express data scientist interview.
FAQs
What’s the average annual salary for a data scientist at American Express?
Average Base Salary
Average Total Compensation
The salary for American Express data scientists ranges between $70k to $143K, with an average of $111K, depending on location and job role.
What other companies are hiring data scientist besides American Express?
Numerous companies are hiring Data Scientists across various industries. Some well-known examples include Google, JPMorgan Chase, and Amazon
Does Interview Query have job postings for American Express data science roles?
Yes, visit our Job Board to check out current opportunities.
Bottom Line
While the American Express data scientist interview process can be demanding, we hope this guide provides valuable support. Best of luck on your journey!