Uploaded March 2026 | Updated September 2026, 5 hours ago
The Data Science Industry doesnβt work the way your bootcamp told you it does. Your $49 Udemy course lied to you. And honestly? Your data science professors probably never worked a real job in their lives.
The "just fill nulls and remove outliers" approach isn't data science - it's cosplay. And if you're still doing it, you're not just wasting time. You're actively making things worse.
After years in the Data Science industry, I'm done sugarcoating it.
In this video, I'll show you:
π― Why duplicate IDs and null customer fields aren't data problems - they're business failures you're too scared to call out
π― The exact reason your "data quality" tickets sit ignored for 8 months (and how to get them fixed in 2 days)
π― Why every time you drop rows or overwrite values, you're destroying evidence like an amateur
π― How to talk to stakeholders, PMs, and engineers who will absolutely try to gaslight you about how the data works
π― The 4 rules that separate data scientists in the Data Science Industry from really well-paid Excel jockeys
If you just finished a bootcamp, landed your first data role, or feel like real-world data is nothing like what you practiced on - this video is for you. It's going to be uncomfortable. Watch it anyway.
π Subscribe for the data science content nobody else wants to say out loud.
___________________________________
π Resources to Level Up Your Data Science Career
π Join our channel for no-BS data science advice : bit.ly/2GsFxmA
π Playlist for more data science interview questions and answers: bit.ly/3jifw81
π Playlist for data science interview tips: bit.ly/2G5hNoJ
π Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
π 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+ds+industry+has+problem
______________________________________________________________________
π Video Timeline:
0:00 βIntro
0:15 β The "Data Cleaning" Myths
0:39 β Messy Data Is a Business Problem, Not Yours to Fix
0:49 β The Investigation Phase (Everyone Has Been Lying to You)
1:28 β Why Data Science Hiring Is Completely Broken
2:21 β How to Stop Being Part of the Problem
2:31 β Rule 1: Demand Context or Don't Touch the Data
2:57 β Rule 2: Speak Money, Not Math
3:37 β Rule 3: Stop Destroying Evidence
4:03 β Rule 4: Document Like You're Building a Legal Case
4:48 β The Hard Truth About Your Job Title
______________________________________________________________________
About StrataScratch:
StrataScratch (platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+ds+industry+has+problem) 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+ds+industry+has+problem. 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.
______________________________________________________________________
π§ Contact Us: Got questions or feedback? Drop them in the comments or email us at team@stratascratch.com.
_____________________________________________________________________
#datascience #datasciencejobs #techcareers #datacleaning #bootcamp
The Data Science Industry doesnβt work the way your bootcamp told you it does. Your $49 Udemy course lied to you. And honestly? Your data science professors probably never worked a real job in their lives.
The "just fill nulls and remove outliers" approach isn't data science - it's cosplay. And if you're still doing it, you're not just wasting time. You're actively making things worse.
After years in the Data Science industry, I'm done sugarcoating it.
In this video, I'll show you:
π― Why duplicate IDs and null customer fields aren't data problems - they're business failures you're too scared to call out
π― The exact reason your "data quality" tickets sit ignored for 8 months (and how to get them fixed in 2 days)
π― Why every time you drop rows or overwrite values, you're destroying evidence like an amateur
π― How to talk to stakeholders, PMs, and engineers who will absolutely try to gaslight you about how the data works
π― The 4 rules that separate data scientists in the Data Science Industry from really well-paid Excel jockeys
If you just finished a bootcamp, landed your first data role, or feel like real-world data is nothing like what you practiced on - this video is for you. It's going to be uncomfortable. Watch it anyway.
π Subscribe for the data science content nobody else wants to say out loud.
___________________________________
π Resources to Level Up Your Data Science Career
π Join our channel for no-BS data science advice : bit.ly/2GsFxmA
π Playlist for more data science interview questions and answers: bit.ly/3jifw81
π Playlist for data science interview tips: bit.ly/2G5hNoJ
π Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
π 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+ds+industry+has+problem
______________________________________________________________________
π Video Timeline:
0:00 βIntro
0:15 β The "Data Cleaning" Myths
0:39 β Messy Data Is a Business Problem, Not Yours to Fix
0:49 β The Investigation Phase (Everyone Has Been Lying to You)
1:28 β Why Data Science Hiring Is Completely Broken
2:21 β How to Stop Being Part of the Problem
2:31 β Rule 1: Demand Context or Don't Touch the Data
2:57 β Rule 2: Speak Money, Not Math
3:37 β Rule 3: Stop Destroying Evidence
4:03 β Rule 4: Document Like You're Building a Legal Case
4:48 β The Hard Truth About Your Job Title
______________________________________________________________________
About StrataScratch:
StrataScratch (platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+ds+industry+has+problem) 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+ds+industry+has+problem. 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.
______________________________________________________________________
π§ Contact Us: Got questions or feedback? Drop them in the comments or email us at team@stratascratch.com.
_____________________________________________________________________
#datascience #datasciencejobs #techcareers #datacleaning #bootcamp
![Data Science SQL Interview Question Walkthrough [Microsoft] - Window Function: Ranking
This Data Science SQL interview question is from Microsoft, and tests your ability to write window functions to rank data. Iβll walk you through solving the question like weβre in an interview and give you some tips on how to approach the solution.
Go to the question through the link below and follow along with me.
Link to the question: https://platform.stratascratch.com/coding/2026-bottom-2-companies-by-mobile-usage?python=&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
π Subscribe to my channel: https://bit.ly/2GsFxmA
π Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
π Playlist for data science interview tips: https://bit.ly/2G5hNoJ
π 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: (0:00βββ)
Interview Question: (0:31ββ)
Framework to solve the problem: (1:25βββ)
Understand your data: (2:33βββ)
Formulate your approach: (5:05βββ)
Code Execution: (7:09βββ)
Code Optimization: (15:54βββ)
Conclusion: (18:10βββ)
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
#MicrosoftDataScienceInterview Data Science SQL Interview Question Walkthrough [Microsoft] - Window Function: Ranking](https://i.ytimg.com/vi/i-E4pdU2qXM/mqdefault.jpg)





![Top Data Science Interview Question And Answer Mistakes 2021 [Asked By Amazon]
Were going to cover the #1 most common mistake made on data science interviews. This mistake is made by both inexperienced and experience data science professionals; it happens both on interviews and in the work setting; and the mistake takes place when trying to solve the most common data science question. Lets cover it so that you dont make the same mistake.
Follow me interactively with the question here: https://platform.stratascratch.com/coding/9915-highest-cost-orders?python=&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
Platforms I recommend to practice data science real scenarios:
- https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link (data science questions)
- https://leetcode.com (general database questions)
- https://datacamp.com (niche specific analytical skillsets)
π Subscribe to my channel: https://bit.ly/2GsFxmA
π Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
π Playlist for data science interview tips: https://bit.ly/2G5hNoJ
π 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)
Description of the most common mistake: (0:34)
Coding example of mistake: (1:00)
How to properly solve the question: (4:50)
Reason why youre making these mistakes: (7:30)
Recommendations to improve: (8:10)
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
#datascience #sqlinterviews #codinginterviews Top Data Science Interview Question And Answer Mistakes 2021 [Asked By Amazon]](https://i.ytimg.com/vi/j8kGqAAIhxA/mqdefault.jpg)



