Uploaded July 2025 | Updated September 2026, 6 hours ago
🔥 Overqualified, Under-Interviewed, and Tired of Being Ghosted?
Welcome to your brutally honest intervention: Data Science Group Therapy.
If you’ve been grinding through job boards, refreshing LinkedIn, and wondering why you’re still invisible despite doing everything right—this session is for you.
In this video, we’ll cover:
✅ The real reason your portfolio isn’t working (and what to build instead)
✅ How to stop sounding like a student and start sounding like a teammate
✅ Why your GitHub, resume, and tech stack might be silently sabotaging you
✅ The cold truth about cold applying — and what to do instead
✅ Exact scripts and project ideas to stand out in 2025’s brutal job market
📌 Like, share, and subscribe if you’re ready to stop guessing and start growing
___________________________________
📚 Resources to Level Up Your Data Science Career
👉 Join our channel for no-BS data science advice : bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+what+no+one+tells+about+ds+interviews
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📅 Video Timeline:
0:00 - Intro: The symptoms
0:38 - Root cause #1: Your projects look academic
1:37 - Root cause #2: Don't translate your stack - mirror their
2:18 - Root cause #3: Your resume looks fake
4:03 - Root cause #4: Your GitHub looks like homework
4:37 - Root cause #5: You're playing the resume lottery
5:16 - Conclusion
______________________________________________________________________
About StrataScratch:
StrataScratch (platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+what+no+one+tells+about+ds+interviews) 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 platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+what+no+one+tells+about+ds+interviews. 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 Us: Got questions or feedback? Drop them in the comments or email us at team@stratascratch.com.
_____________________________________________________________________
#datascience #datascienceinterview #machinelearning #dataanalytics #sql #python #datasciencejobs #techcareers #interviewtips #codinginterview #memes #machinelearningengineer #careeradvice #datascientists #techinterviewprep #faang #trending #coding #interviewtips #interview
🔥 Overqualified, Under-Interviewed, and Tired of Being Ghosted?
Welcome to your brutally honest intervention: Data Science Group Therapy.
If you’ve been grinding through job boards, refreshing LinkedIn, and wondering why you’re still invisible despite doing everything right—this session is for you.
In this video, we’ll cover:
✅ The real reason your portfolio isn’t working (and what to build instead)
✅ How to stop sounding like a student and start sounding like a teammate
✅ Why your GitHub, resume, and tech stack might be silently sabotaging you
✅ The cold truth about cold applying — and what to do instead
✅ Exact scripts and project ideas to stand out in 2025’s brutal job market
📌 Like, share, and subscribe if you’re ready to stop guessing and start growing
___________________________________
📚 Resources to Level Up Your Data Science Career
👉 Join our channel for no-BS data science advice : bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+what+no+one+tells+about+ds+interviews
______________________________________________________________________
📅 Video Timeline:
0:00 - Intro: The symptoms
0:38 - Root cause #1: Your projects look academic
1:37 - Root cause #2: Don't translate your stack - mirror their
2:18 - Root cause #3: Your resume looks fake
4:03 - Root cause #4: Your GitHub looks like homework
4:37 - Root cause #5: You're playing the resume lottery
5:16 - Conclusion
______________________________________________________________________
About StrataScratch:
StrataScratch (platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+what+no+one+tells+about+ds+interviews) 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 platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+what+no+one+tells+about+ds+interviews. 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 Us: Got questions or feedback? Drop them in the comments or email us at team@stratascratch.com.
_____________________________________________________________________
#datascience #datascienceinterview #machinelearning #dataanalytics #sql #python #datasciencejobs #techcareers #interviewtips #codinginterview #memes #machinelearningengineer #careeradvice #datascientists #techinterviewprep #faang #trending #coding #interviewtips #interview
![[Part 1]: Exploring and Visualizing Data For A Facebook Data Science Project of Movie Ratings](https://i.ytimg.com/vi/cM12QtrhdLo/mqdefault.jpg "[Part 1]: Exploring and Visualizing Data For A Facebook Data Science Project of Movie Ratings
Join us as we dive into a data science project from Facebook to predict Rotten Tomatoes movie ratings. We explored two different approaches. In the first approach, we focus on using numerical and categorical features, while in the second approach, we analyze the sentiment of movie reviews. Throughout the video, we compare our models predictions to actual data to evaluate their performance. By the end of this series, youll have a deeper understanding of how Rotten Tomatoes movie ratings can be predicted and gain valuable insights into machine learning techniques. Dont forget to subscribe to stay tuned and learn more about data science.
Watch the full tutorial:
📌[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
Go to the project through the link below and follow along with me👇
https://platform.stratascratch.com/data-projects/rotten-tomatoes-movies-rating-prediction?utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+1
👉 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+1
Timeline:
Intro: (0:00)
Take-home assignment: (0:09)
Exploring the data: (1:48)
Summary of the data: (4:53)
Content rating variable visualization: (5:22)
Audience status visualization: (6:40)
Distribution of each audience status category: (7:04)
Take away: (10:03)
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+1), 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+1. 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 me, 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
#datascienceproject")
![Tricky Data Science Interview Question [By Facebook]](https://i.ytimg.com/vi/eC7MdwKCCOE/mqdefault.jpg "Tricky Data Science Interview Question [By Facebook]
Today well cover a tricky data science interview question asked by Facebook. Its not so much a tricky problem as it is a problem with a non-obvious solution. But these types of questions are asked all the time on interviews because theyre scenarios that youd have to handle everyday as a data scientist. Lets cover what this questions all about. Follow along with me by going to the question below.
Link to question: https://platform.stratascratch.com/coding/10064-highest-energy-consumption?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.
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
Timestamps:
Intro: (0:00)
Question: (1:40)
Exploring the datasets: (2:03)
The 1st trick!: (2:40)
Write out approach: (4:34)
The 2nd trick!: (5:35)
Coding the solution: (6:35)
Conclusion: (10:50)
About The Platform:
Im using StrataScratch, 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
#sql #datascience #sqlinterviews")
