Paypal Interview Questions
Practice the exact questions companies are asking right now.
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Design and evaluate a fraud detection strategy
Context You are interviewing for a Fraud Data Scientist role at a payments company. The company has a fraud model and some operational constraints. Pa...
Explain list vs tuple in Python
Question In Python: 1. What are the key differences between a list and a tuple? 2. When would you prefer using a tuple over a list? 3. What are the pe...
How to evaluate a new homepage feature
Scenario PayPal plans to launch a new homepage feature (e.g., a new CTA module, personalized content, or a redesigned layout). You are asked to evalua...
Explain and interpret p-values correctly
Context You are evaluating a change to a fraud decision rule (e.g., a new threshold or step-up authentication rule). You run an experiment comparing C...
Solve common search/parse/graph frequency tasks
You are given several independent coding tasks. For each task, write a function that returns the required output. 1) Find insertion index in a sorted ...
Compute variance of a list in Python
Task Given a Python list of numbers (ints/floats), write code to compute its variance. Requirements - Input: nums: list[float] (length \(n\ge 1\)) - C...
Interpret p-values and common pitfalls
In a Fraud Data Science interview, you are asked “some p-value questions.” Answer the following in a fraud/experimentation context: 1) Define a p-valu...
Detect credit-card transaction fraud
Credit-Card Fraud Detection: Decisions and System Design Context You are designing a real-time decisioning system for card transactions with strict la...
Write SQL using HAVING and window functions
Context You work on fraud analytics. Assume the following schema (PostgreSQL-like types): transactions - txn_id BIGINT (PK) - merchant_id BIGINT - use...
Design a traditional fraud detection system
Design an End-to-End Real-Time Payments Fraud Detection System Context: You are designing a fraud detection system for a large-scale online payments p...
Explain confounding with an Uber example
Question In the context of analyzing Uber/Uber Eats data, explain what a confounding effect is. 1. Define confounder and why it can bias an observed r...
Explain fraud types and evaluate a fraud model
You are interviewing for a Fraud Data Scientist role at PayPal. Answer the following: 1) List common fraud types relevant to payments (e.g., account t...
Explain differences between Python list and tuple
In Python, what are the key differences between a list and a tuple? Cover: - Mutability and implications - Performance and memory considerations (high...
Find k most frequent in linear time
Given an integer array nums and an integer k (1 ≤ k ≤ number of distinct values in nums), return any k values that appear most frequently. Implement a...
Should you play a dice payout game?
Two players each roll a fair six-sided die once. - If you win (your roll > opponent’s roll), the opponent pays you $n. - If the opponent wins or it’s ...
Build a real-time ATO model
End-to-end ML Case: Real-time Detection of Venmo Account Takeover (ATO) at Authorization Context Design a real-time machine learning system that score...
Optimize thresholds under fraud costs
Cost-sensitive Thresholding for Fraud (ATO) Classifier Context You are evaluating a binary classifier for account takeover (ATO) fraud on a large vali...
Design and Analyze A/B Test for Cashback Program
A/B Test Design: Checkout Cashback Program (PayPal) Scenario PayPal plans to launch a checkout cashback program (e.g., "Get 1–5% back when you pay wit...
Write SQL for top drivers and cancellation rates
You work on a rideshare product with airport pickups. Using SQL, answer the questions below. Assume all timestamps are stored in UTC. Define the analy...
Answer career, manager, and team fit questions
Behavioral Questions Answer the following questions in a structured, interview-ready way: 1. Project deep dive: Walk me through a project you worked o...