3 Painful Mistakes I Made as a Junior Data Scientist
Learn from them to fast-track your career today
Becoming a data scientist isn’t just about crunching numbers — it’s about navigating a minefield of potential missteps.
On my journey, I made some blunders that were not only painful but also incredibly enlightening. Here are the top three mistakes I made, so you don’t have to learn the hard way.
Hello there!
I’m Mandy Liu, an ex-Meta data scientist :)
I studied Economics, started my career in Consulting, and transitioned into the fascinating world of Data Science and solopreneurship.
I run a weekly newsletter where I write about data science, artificial intelligence, business and entrepreneurship. Be sure to subscribe! ⬇️
1. Concealing weaknesses
I used to believe I had to excel at everything to be the perfect data scientist — the one who knew every detail about A/B testing and the latest ML models.
