Uploaded April 2021 | Updated September 2026, 1 week ago
In this video I highlight the main reasons why it is unlikely that you will become a data scientist. TO BE CLEAR I still think it is possible for anyone to break into this field, but I also think it is important to set realistic expectations.
Subscribe to the Newsletter here! kennethjee.com/newsletter
1) Educational Burden - Data science is a multidisciplinary field. You need to learn computer science, coding, and subject area knowledge. You really need to invest many hours into this endeavor.
- Project Playlist: youtube.com/playlist?list=PL2zq7klxX5AReJn7nZfqOKLZ3IpKj7fwc
- Kaggle Courses (Free): kaggle.com/learn/overview
- 365 Data Science (57% Discount): 365datascience.pxf.io/P0jbBY
2) Market Saturation - There is a huge supply of entry level data scientists. With more people, that means the probability of landing a data science job is lower.
3) Data Science isn't a good fit for you - It takes a lot of time and dedication to break into this field. It helps to be very passionate about the work. There are other great careers like software engineering that have a lower barrier to entry where you make similar income (if not more).
4) Ambiguity - Data science job postings are very unclear / unreliable.
5) Continued learning - You need to be adaptable in your role. It takes habits or huge motivation to keep studying.
Congratulations! If you made it this far you likely have one of the most important skills for breaking into this field.
That skill is GRIT.
Grit book: amzn.to/3wBez1H
0:00 Intro
0:45 Challenge 1
1:50 Challenge 2
2:55 Challenge 3
3:49 Challenge 4
5:19 Challenge 5
6:10 GOOD NEWS!
7:00 What's Next?
8:22 Blooper
#DataScience #KenJee
β Subscribe: youtube.com/c/kenjee1?sub_confirmation=1
π Listen to My Podcast: youtube.com/c/KensNearestNeighborsPodcast
πΈ Check out My Website - kennethjee.com
π Books and Products I use - amazon.com/shop/kenjee (affiliate link)
Partners & Affiliates
π Interview Query - interviewquery.com/?ref=kenjee
MORE DATA SCIENCE CONTENT HERE:
π€My Twitter - twitter.com/KenJee_DS
π LinkedIn - linkedin.com/in/kenjee
π Kaggle - kaggle.com/kenjee
π Medium Articles - medium.com/@kenneth.b.jee
π» Github - github.com/PlayingNumbers
π My Sports Blog -playingnumbers.com
Check These Videos Out Next!
My Leaderboard Project: youtube.com/watch?v=myhoWUrSP7o&ab_channel=KenJee
66 Days of Data: youtube.com/watch?v=qV_AlRwhI3I&ab_channel=KenJee
How I Would Learn Data Science in 2021: youtube.com/watch?v=41Clrh6nv1s&ab_channel=KenJee
My Playlists
Data Science Beginners: youtube.com/playlist?list=PL2zq7klxX5ATMsmyRazei7ZXkP1GHt-vs
Project From Scratch: youtube.com/watch?v=MpF9HENQjDo&list=PL2zq7klxX5ASFejJj80ob9ZAnBHdz5O1t&ab_channel=KenJee
Kaggle Projects: youtube.com/playlist?list=PL2zq7klxX5AQXzNSLtc_LEKFPh2mAvHIO
In this video I highlight the main reasons why it is unlikely that you will become a data scientist. TO BE CLEAR I still think it is possible for anyone to break into this field, but I also think it is important to set realistic expectations.
Subscribe to the Newsletter here! kennethjee.com/newsletter
1) Educational Burden - Data science is a multidisciplinary field. You need to learn computer science, coding, and subject area knowledge. You really need to invest many hours into this endeavor.
- Project Playlist: youtube.com/playlist?list=PL2zq7klxX5AReJn7nZfqOKLZ3IpKj7fwc
- Kaggle Courses (Free): kaggle.com/learn/overview
- 365 Data Science (57% Discount): 365datascience.pxf.io/P0jbBY
2) Market Saturation - There is a huge supply of entry level data scientists. With more people, that means the probability of landing a data science job is lower.
3) Data Science isn't a good fit for you - It takes a lot of time and dedication to break into this field. It helps to be very passionate about the work. There are other great careers like software engineering that have a lower barrier to entry where you make similar income (if not more).
4) Ambiguity - Data science job postings are very unclear / unreliable.
5) Continued learning - You need to be adaptable in your role. It takes habits or huge motivation to keep studying.
Congratulations! If you made it this far you likely have one of the most important skills for breaking into this field.
That skill is GRIT.
Grit book: amzn.to/3wBez1H
0:00 Intro
0:45 Challenge 1
1:50 Challenge 2
2:55 Challenge 3
3:49 Challenge 4
5:19 Challenge 5
6:10 GOOD NEWS!
7:00 What's Next?
8:22 Blooper
#DataScience #KenJee
β Subscribe: youtube.com/c/kenjee1?sub_confirmation=1
π Listen to My Podcast: youtube.com/c/KensNearestNeighborsPodcast
πΈ Check out My Website - kennethjee.com
π Books and Products I use - amazon.com/shop/kenjee (affiliate link)
Partners & Affiliates
π Interview Query - interviewquery.com/?ref=kenjee
MORE DATA SCIENCE CONTENT HERE:
π€My Twitter - twitter.com/KenJee_DS
π LinkedIn - linkedin.com/in/kenjee
π Kaggle - kaggle.com/kenjee
π Medium Articles - medium.com/@kenneth.b.jee
π» Github - github.com/PlayingNumbers
π My Sports Blog -playingnumbers.com
Check These Videos Out Next!
My Leaderboard Project: youtube.com/watch?v=myhoWUrSP7o&ab_channel=KenJee
66 Days of Data: youtube.com/watch?v=qV_AlRwhI3I&ab_channel=KenJee
How I Would Learn Data Science in 2021: youtube.com/watch?v=41Clrh6nv1s&ab_channel=KenJee
My Playlists
Data Science Beginners: youtube.com/playlist?list=PL2zq7klxX5ATMsmyRazei7ZXkP1GHt-vs
Project From Scratch: youtube.com/watch?v=MpF9HENQjDo&list=PL2zq7klxX5ASFejJj80ob9ZAnBHdz5O1t&ab_channel=KenJee
Kaggle Projects: youtube.com/playlist?list=PL2zq7klxX5AQXzNSLtc_LEKFPh2mAvHIO










![How I Built a Profitable AI Product in 43 Days
I built my SaaS Newsletter Hero in 43 days in order to prepare for the massive AI disruption I see coming. This was my process, the lows and the highs.
Check it out here: https://www.newsletterhero.ai/
Code: BETA45 ($99 for the full year - more than 50% off the monthly rate)
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07:45 Day 35: First Paying Customer - Customer acquired through Reddit comment on micro-SaaS celebration post - Validation moment: Stranger paid for the product - Customer feedback immediately integrated, especially onboarding improvements
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