what it’s ACTUALLY like to work at FAANG... (Facebook/Meta, Amazon, Netflix, Google, Apple) This video is sponsored by BetterHelp. Check out BetterHelp at https://betterhelp.com/TinaHuangIn this video, I talk about why people want to work at FAANG/MANGA and offer an internal perspective as a data scientist that works at one of these companies (Facebook/Meta, Amazon, Netflix, Google, Apple)Mayuko's great video: https://www.youtube.com/watch?v=ZxCUnxwR89Q&t=1s⏰ Timestamps ========================00:00 intro 01:44 pay & perks 07:39 pay & perks caveats 08:19 prestige 09:54 prestige caveats 10:16 calibre 12:29 calibre caveats 13:57 THING THAT PEOPLE DON'T CONSIDER 18:04 is it worth it? 🎥 My filming setup ========================📷 camera: https://amzn.to/3LHbi7N🎤 mic: https://amzn.to/3LqoFJb🔭 tripod: https://amzn.to/3DkjGHe💡 lights: https://amzn.to/3LmOhqk🔗Affiliates========================365 Data Science: https://bit.ly/3tIUBCY (link for 57% discount for their complete data science training)Check out StrataScratch for data science interview prep: https://stratascratch.com/?via=tina📲Socials ========================instagram: https://www.instagram.com/hellotinah/linkedin: https://www.linkedin.com/in/tinaw-h/ discord: https://discord.gg/5mMAtprshX🤯Study with Tina ========================Study with Tina channel:https://www.youtube.com/channel/UCI8JpGrDmtggrryhml8kFGwHow to make a studying scoreboard: https://www.youtube.com/watch?v=KAVw910mIrIScoreboard website: scoreboardswithtina.comlivestreaming google calendar:https://bit.ly/3wvPzHB🎥Other videos you might be interested in========================How I consistently study with a full time job:https://www.youtube.com/watch?v=INymz5VwLmkHow I would learn to code (if I could start over): https://www.youtube.com/watch?v=MHPGeQD8TvI&t=84s🐈‍⬛🐈‍⬛About me ========================Hi, my name is Tina and I'm a data scientist at a FAANG company. I was pre-med studying pharmacology at the University of Toronto until I finally accepted that I would make a terrible doctor. I didn't know what to do with myself so I worked for a year as a research assistant for a bioinformatics lab where I learned how to code and became interested in data science. I then did a masters in computer science (MCIT) at the University of Pennsylvania before ending up at my current job in tech :) 📧Contact========================youtube: youtube comments are by far the best way to get a response from me! linkedin: https://www.linkedin.com/in/tinaw-h/ email for business inquiries only: [email protected] ========================Some links are affiliate links and I may receive a small portion of sales price at no cost to you. I really appreciate your support in helping improve this channel! :) Follow this podcast to get Tina Huang’s insights in audio format, perfect for learning on the go. Tina Huang on YouTube: https://www.youtube.com/@TinaHuang1Disclaimer: This podcast is an independent audio adaptation of content originally created by Tina Huang. It was made by a viewer who values her insights and aims to make them more accessible for audio-first learners. This is not an official production of Tina Huang, and it is not affiliated with or endorsed by her. All rights to the original video content remain with Tina Huang. If you represent Tina and would like to discuss this project, please don’t hesitate to get in touch. - Learn more about your ad choices. Visit megaphone.fm/adchoices

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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