Uploaded April 2022 | Updated September 2026, 59 minutes ago
In this video, we'll take a close look at one of the PayPal data scientist interview questions and discuss two different ways of solving this question using SQL. We’ll also compare these two approaches and find out which is the best for you to use if you’re at a job interview.
Link to the questions: platform.stratascratch.com/coding/9901-super-managers?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
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👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
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Timeline:
Intro: (0:00)
Understanding the data: (1:02)
Solution 1: Formulate the approach: (1:44)
Solution 1: Code execution: (2:26)
Solution 2: Formulate the approach: (3:42)
Solution 2: Code execution: (4:17)
Comparison: (6:11)
Conclusion: (6:57)
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About The Platform:
I'm using StrataScratch (platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.
______________________________________________________________________
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
______________________________________________________________________
In this video, we'll take a close look at one of the PayPal data scientist interview questions and discuss two different ways of solving this question using SQL. We’ll also compare these two approaches and find out which is the best for you to use if you’re at a job interview.
Link to the questions: platform.stratascratch.com/coding/9901-super-managers?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
______________________________________________________________________
👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
______________________________________________________________________
Timeline:
Intro: (0:00)
Understanding the data: (1:02)
Solution 1: Formulate the approach: (1:44)
Solution 1: Code execution: (2:26)
Solution 2: Formulate the approach: (3:42)
Solution 2: Code execution: (4:17)
Comparison: (6:11)
Conclusion: (6:57)
______________________________________________________________________
About The Platform:
I'm using StrataScratch (platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.
______________________________________________________________________
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
______________________________________________________________________
![Advanced Facebook Data Science SQL interview question [RANK()]](https://i.ytimg.com/vi/PlpUo6bHsBQ/mqdefault.jpg "Advanced Facebook Data Science SQL interview question [RANK()]
This advanced SQL question is from the Facebook data science interview that tests your ability to write window functions and rank data and use some advanced functions like coalesce. It’s a complicated question that involves subqueries and joins and also tests your knowledge in rankings.
Link to the question to follow along with me: https://platform.stratascratch.com/coding/2007-rank-variance-per-country?python=&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
Timeline:
Intro: (0:00)
Interview Question: (0:33)
Framework to solve the problem: (0:58)
Understand your data: (2:18)
Formulate your approach: (5:38)
Code Execution: (8:42)
Conclusion: (23:05)
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
#FacebookDataScienceInterview")
![Advanced Data Science SQL Interview Question [Amazon] (window functions & aliasing)](https://i.ytimg.com/vi/QenwDm5oWdU/mqdefault.jpg "Advanced Data Science SQL Interview Question [Amazon] (window functions & aliasing)
This SQL data science interview question was asked by Amazon and will test your date manipulation and window function skills. I’ll cover both the question and walk you through the approach. I’ll also talk about my 4 step approach to solving any data science interview question. This is literally how I would answer every data science interview question and prepare for every data science interview at FAANG companies and others.
Link to the question: https://platform.stratascratch.com/coding/10319-monthly-percentage-difference?python=&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
This series is for both beginner and intermediate data scientists and analysts interested in learning how to solve common data science interview questions in SQL. These are real data science interview questions. For some background context and an intro about what this series is about: https://bit.ly/36kKbxG
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
Timeline:
Intro: (0:00)
Question: (1:18)
4-Step framework to solve the question: (2:02)
Explore underlying data: (2:18)
Identify required columns: (3:45)
Visualize the output: (4:12)
Build solution step-by-step and test: (4:44)
Coding: (4:57)
Format data to YYYY-MM: (6:27)
Calculate current months revenue: (7:46)
Calculate previous months revenue: (8:36)
Aggregate to year-month: (10:25)
Implement month-over-month difference formula: (11:26)
Apply a window alias: (13:15)
Clean up formatting: (14:06)
Conclusion: (14:50)
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
#datascienceinterview #sqlinterviews")
![Data Project: Analyzing Review Sentiment for Accurate Ratings [Part 1]](https://i.ytimg.com/vi/Qh9ajFNeIEc/mqdefault.jpg "Data Project: Analyzing Review Sentiment for Accurate Ratings [Part 1]
Welcome to the second series of the Facebook data science project for predicting movie ratings! In this video, we explore building a high-performance classification algorithm to predict movie ratings. We merge two data sets, focusing on review sentiment to determine whether a movie is labeled as Rotten or Fresh. Join us as we preprocess the data, analyze the distribution of review types, and implement a random forest model. Dont forget to subscribe and stay tuned for the next video in our series!
Go to the project through the link below and follow along with us👇
https://platform.stratascratch.com/data-projects/rotten-tomatoes-movies-rating-prediction?utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+s2+p1
Watch the previous videos from the first series:
📌 [Part 1]: Exploring and Visualizing Data For A Facebook Data Science Project of Movie Ratings: https://youtu.be/cM12QtrhdLo
📌[Part 2]: Exploring Decision Tree Classifiers For A Facebook Data Science Project of Movie Ratings: https://youtu.be/Ih6G5hnn30Q
📌 [Part 3]: Random Forest Classifier For A Facebook Data Science Project of Movie Ratings: https://youtu.be/J4rheMtvu6g
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Playlist for data science projects: https://bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+s2+p1
Timeline:
Intro: (0:00)
Take-home assignment: (0:18)
Approaches review: (0:31)
Preparing the dataset: (1:10)
Using the head method for data review: (2:34)
Encoding the labels into integer representation: (3:45)
Splitting the dataset into train and test sets: (4:30)
Tokenization in NLP: (4:53)
Using a random forest classifier: (6:21)
Improving the models performance: (7:33)
Take away: (9:24)
About The Platform:
StrataScratch (https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+s2+p1) is a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+s2+p1. All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from the StrataScratch team, you can use ss15 for a 15% discount on the premium plans.
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email us at team@stratascratch.com
#datascienceproject")
![Data Preparation for Modeling [DoorDash Data Science Project]](https://i.ytimg.com/vi/Sf6jn8QZHhc/mqdefault.jpg "Data Preparation for Modeling [DoorDash Data Science Project]
This video will walk you through the DoorDash Delivery Duration Prediction data project. Well cover all the stages of the preparation of data for modeling.
🧑💻 Go to the project through the link below and follow along with me: https://platform.stratascratch.com/data-projects/delivery-duration-prediction?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
Watch the next parts:
📌 Part 2: Collinearity and Removing Redundancies: https://youtu.be/m3zEV10qvE8
📌 Part 3: Multicollinearity and Feature Selection: https://youtu.be/gh5JzALBQvU
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
Timeline:
Intro: (0:00)
Take-home assignment from DoorDash: (0:10 )
Exploring and understanding the data: (0:47)
Coding the solution: (2:05)
Feature Creation (3:10)
Data Preparation for Modeling (5:34)
Conclusion: (10:16)
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
#StrataScratch #DoordashDataProject #DataModeling")
