Uploaded February 2024 | Updated September 2026, 18 minutes ago
Discover the evolving landscape of data science careers in this insightful video! From the once-generalist role of data scientists to today's specialized positions, we delve into the key specializations employers are seeking. Whether you're interested in becoming a data engineer, data scientist, machine learning engineer, business/data analyst, or business intelligence engineer, we've got you covered with essential skills and responsibilities. Learn how each role contributes to the data-driven decision-making process and find out how to carve your path in this dynamic field.
Don't miss out—subscribe for more valuable insights and visit stratascratch.com for additional data science resources!
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👉 Subscribe to the 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
👉 Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+ml+vs+de+vs+ds
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Timeline:
Intro: (0:00)
Data Engineer: (1:01)
Data Scientist: (2:45)
Machine Learning Engineer: (4:42)
Business/Data Analyst: (6:27)
Business Intelligence Engineer: (7:43)
Conclusion: (9:15)
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About The Platform:
StrataScratch (platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+ml+vs+de+vs+ds) 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=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+ml+vs+de+vs+ds. 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
______________________________________________________________________
#datascientist #datascience #datasciencecareer #dataanalysis #machinelearningengineer #businessintelligenceengineer #dataanalyst
Discover the evolving landscape of data science careers in this insightful video! From the once-generalist role of data scientists to today's specialized positions, we delve into the key specializations employers are seeking. Whether you're interested in becoming a data engineer, data scientist, machine learning engineer, business/data analyst, or business intelligence engineer, we've got you covered with essential skills and responsibilities. Learn how each role contributes to the data-driven decision-making process and find out how to carve your path in this dynamic field.
Don't miss out—subscribe for more valuable insights and visit stratascratch.com for additional data science resources!
______________________________________________________________________
👉 Subscribe to the 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
👉 Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+ml+vs+de+vs+ds
______________________________________________________________________
Timeline:
Intro: (0:00)
Data Engineer: (1:01)
Data Scientist: (2:45)
Machine Learning Engineer: (4:42)
Business/Data Analyst: (6:27)
Business Intelligence Engineer: (7:43)
Conclusion: (9:15)
______________________________________________________________________
About The Platform:
StrataScratch (platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+ml+vs+de+vs+ds) 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=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+ml+vs+de+vs+ds. 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
______________________________________________________________________
#datascientist #datascience #datasciencecareer #dataanalysis #machinelearningengineer #businessintelligenceengineer #dataanalyst
![Meta Product Families: head() Function to Explore the Data [Part 1]](https://i.ytimg.com/vi/9quwCoQ6CoU/mqdefault.jpg "Meta Product Families: head() Function to Explore the Data [Part 1]
If youre looking for help working with a dataset, then this video is for you! Well be using the head() function to explore the data in the Meta Product Families interview question, so that you can find out any missing values.
Part 2: https://www.youtube.com/shorts/yoUO84tOH3c
Go to the question through the link below and follow along with me👇
Link to the question: https://platform.stratascratch.com/coding/2123-product-families?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
👉 Watch the full video: https://youtu.be/RmMuS5iiviI
👉 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
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
#DataAnalytics #PythonInterviewQuestions #Stratascratch")
![Data Ranking: Python Pandas and SQL Equivalents [Part 2]](https://i.ytimg.com/vi/Cg66PLiW9L0/mqdefault.jpg "Data Ranking: Python Pandas and SQL Equivalents [Part 2]
In this video, we dive deeper into ranking methods and functions in Python using data frames. We discuss additional parameters that can help refine the ranking function, making it more flexible and adaptable to different data sets. We also explore the SQL equivalence of ranking methods, which will be helpful for those familiar with SQL.
👉 Watch our previous tutorial:
How to Rank() Your Data In Python Pandas [Part 1]: https://youtu.be/2uu0prXMhfU
🧑💻 Go to the questions through the links below and follow along with us:
📌 Question 1: https://platform.stratascratch.com/coding/9611-find-the-80th-percentile-of-hours-studied?code_type=2&utm_source=youtube&utm_medium=click&utm_campaign=YT+python+sql+ranking
📌 Question 2: https://platform.stratascratch.com/coding/10160-rank-guests-based-on-their-ages?code_type=2&utm_source=youtube&utm_medium=click&utm_campaign=YT+python+sql+ranking
📌 Question 3: https://platform.stratascratch.com/coding/10161-ranking-hosts-by-beds?code_type=2&utm_source=youtube&utm_medium=click&utm_campaign=YT+python+sql+ranking
📌 Question 4: https://platform.stratascratch.com/coding/10351-activity-rank?code_type=2&utm_source=youtube&utm_medium=click&utm_campaign=YT+python+sql+ranking
👉 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?utm_source=youtube&utm_medium=click&utm_campaign=YT+python+sql+ranking
Timeline:
Intro: (0:00)
Percentage Ranking in Python: (0:43)
Ranking in SQL: (4:10)
Conclusion: (7:26)
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+python+sql+ranking), 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+python+sql+ranking. 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
#pandaspythontutorial #pythondatascience #sqlrank")
