Introduction
As a leading global e-commerce platform empowering millions of businesses, Shopify seeks candidates who can drive innovation in digital commerce. Shopify OA is a critical step in its recruitment process, designed to evaluate technical skills, problem-solving efficiency, and algorithmic thinking. This guide breaks down the OA structure, common question types, and provides three coding practice questions to help you prepare effectively. guide breaks down the OA structure, common question types, and provides three coding practice questions to help you prepare effectively.
Shopify OA Interview Process
1. Resume Screening
Shopify's recruiters review resumes to shortlist candidates with relevant technical skills (e.g., Python, JavaScript, Ruby), project Strong foundations in web development, data structures, or machine learning ("for specific roles") are highly valued. Strong foundations in web development, data structures, or machine learning ( for specific roles) are highly valued.
2. OA
The OA typically includes 2-3 coding problems Questions mirror real-world e-commerce scenarios, such as order processing, inventory management, or recommendation systems. Questions mirror real-world e-commerce scenarios, such as order processing, inventory management, or recommendation systems. The assessment is timed (60-90 minutes), testing both correctness and speed.
3. Follow-Up Interviews
Candidates who excel in the OA progress to technical and behavioral interviews. These may involve live coding, system design discussions (for senior roles), or case studies evaluating teamwork and problem-solving approaches. These may involve live coding, system design discussions (for senior roles), or case studies evaluating teamwork and problem-solving approaches.
Shopify OA Interview Question Types
1. Algorithmic Coding
Common themes include optimizing e- commerce workflows, inventory allocation, or user behavior analysis. commerce workflows, inventory allocation, or user behavior analysis.
2. Data Manipulation
Tasks involving string/array operations, graph traversal, or statistical calculations relevant to e-commerce data (e.g., order fulfillment, sales trends).
3. System Design (Implicit in Some Questions)
While not always explicit, some OA problems test scalability and design thinking (e.g., handling large datasets or concurrent user interactions).
Shopify OA Coding Practice Questions
Question 1: Inventory Allocation Optimization
Problem Statement:
Given a list of orders with item quantities and a list of warehouses with available stock, allocate items to minimize unfulfilled orders. Each warehouse can fulfill orders sequentially, and once a warehouse's stock is exhausted, it cannot fulfill further orders. can fulfill orders sequentially, and once a warehouse's stock is exhausted, it cannot fulfill further orders. Return the number of Return the number of unfulfilled items.
Example Input:
orders = [3, 5, 4]
warehouses = [8, 2, 5]Output:1
Question 2: Discounted Price Calculation
Problem Statement:
Calculate the final price of items in a shopping cart after applying tiered discounts. Each item has a base price and a quantity. Discounts apply if the total quantity of an item exceeds a threshold. For example, "Buy 2, get 1 free" (3 items cost the price of 2). Return the total cost.
Example Input:
items = [
{"price": 10, "quantity": 5, "discount": (3, 2)}, # Buy 3, pay for 2
{"price": 20, "quantity": 2, "discount": None}
]Output:10*(4) + 20*2 = 80
Question 3: Product Recommendation Engine
Problem Statement:
Given a matrix where purchases[i][j] = 1 if user i bought product j, generate top 3 recommendations for each user based on co-occurrence (products bought together by other users). Exclude products the user has already purchased.
Example Input:
purchases = [
[1, 0, 1], # User 0 bought products 0 and 2
[0, 1, 1], # User 1 bought products 1 and 2
[1, 1, 0] # User 2 bought products 0 and 1
User 2 bought products 0 and 1]Output:
[
[1], # User 0: recommend product 1 (bought with 2 by User 1)
[0], # User 1: recommend product 0 (bought with 2 by User 0)
[2] # User 2: recommend product 2 (bought with 0/1 by others)
]Hundreds of Success Stories-You're Next!
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