Just did it yesterday. Wayfair Data Scientist OA, the overall feeling is much friendlier than expected, the pace is clear, the question type is on the practical side. The entire exam is 105 minutes long, with 3 questions, including SQL, Python Pandas and a Case Study, all of which are very close to the actual work.
Question 1: SQL
Table. weather
Columns.
Datecitytemperature
Task.
Write a query to calculate the average temperature per city and classify each record into one of three categories.
'High'if temperature > 80'Normal'if 60 ≤ temperature ≤ 80'Low'if temperature < 60
Then, compute the average temperature difference per city.
Key points.
- Use
CASE WHENto create the temperature category column. - Use
AVG()withGROUP BY cityto summarize results. - Rename output columns properly since Wayfair's grader checks them strictly.
Tip: This is a very standard SQL aggregation question that focuses on logic and details.
Question 2: Pandas
Task.
Given a dataset with missing numeric values, fill missing entries using the median of each column instead of the mean.
Then, group the data by a categorical variable (e.g., region) and calculate summary statistics such as mean And count.
Example steps.
import pandas as pd
import numpy as np
df = pd.read_csv("data.csv")
df = df.fillna(df.median(numeric_only=True))
summary = df.groupby("region").agg({"sales": "mean", "order_id": "count"})
Focus: The title explicitly calls for the use of median Dealing with missing values, many people habitually write mean, and it is easy to deduct points here.
Wayfair's OA environment is an online Jupyter notebook, you need to write the code and click "Run" to output the final result. Don't forget to import the package or you will get an error.
Question 3: Case Study
Scenario.
You are given data on customer complaints, including columns like.
complaint_type(Late delivery,Product damaged,Customer unsatisfied)resolution(Refund,Replacement,Discount)Datedepartment
Questions.
- Provide 3 insights You can draw from the data.
- Provide 3 recommendations based on your insights.
- Choose one prioritized recommendation, and explain.
- How you would measure the success of this recommendation.
- What risks are associated with implementing it.
This part is more oriented towards business analysis and examines logical closure and communication skills. For example:
- If "Late delivery" is the most frequent complaint type, optimization of the logistics supply chain can be recommended.
- If the satisfaction level of the "Refund" resolution is low, the refund process can be optimized or changed to replacement.
- Measurements can be customer satisfaction, NPS or repeat complaint rates.
Overall Impression
This OA is very close to the daily work of a Data Scientist.
While SQL and Pandas look at the technical fundamentals, Case Study looks at how well you can translate your analytics into actionable recommendations.
The recommended allocation of time is as follows:
- SQL: 20 minutes
- Pandas: 25 minutes
- Case Study: 60 minutes
The text part of the case should be concise and logical, do not need to pile up fancy vocabulary, clear thinking is the most important.
Wrap-up
Wayfair DS OA is a very representative real-world question.
It doesn't test algorithms, it tests how you can start with data and come up with actionable business conclusions.
If you can do "Insight → Recommendation → Measurement → Risk" four-step closure in Case, you can basically get a high score.
Programhelp Aide Memoire
Our Programhelp team has recently helped a number of students successfully get DS OA's from Wayfair, DoorDash, Instacart, Capital One, and more.
Wayfair This comprehensive test is a special test of time allocation and answer thinking.
Our Programhelp team's no-trace online service is designed for this scenario:
Full remote collaborative ghostwriting: Real-time code writing over a secure connection, with your interface completely under your control.
No records in the system: We use stealth mode signaling without modifying system processes or leaving logs.
Tested safety is tested: Wayfair, Amazon, TikTok, Capital One and other multi-platform tests have passed multiple rounds of validation without any risk of being detected by the system.
Real-time voice prompts: When you get stuck in the logic, we voice prompt key ideas (e.g., SQL logical structure, Pandas call order, Case framework construction) to ensure smooth pacing.
This type of OA is essentially a time-limited stress test rather than an examination of rote memorization.
Programhelp's helper approach allows you to focus on understanding the logic and outputting quality answers with ease.
