Summary
Marketers are increasingly voicing concerns about "bull spend," a term used to describe advertising budgets allocated to metrics that appear impressive until scrutinized by financial officers. This issue is highlighted in discussions among professionals who share their experiences and frustrations in online communities. The conversation emphasizes the need for marketers to focus on genuine brand impact rather than superficial metrics.
In the realm of data science, individuals transitioning from other fields face challenges in securing jobs despite having relevant skills. The key to overcoming these obstacles lies in demonstrating the ability to drive real-world impact through data projects. Those currently employed are encouraged to engage in data-related tasks within their existing roles, while job seekers can benefit from open-source projects and consulting gigs to build their portfolios.
Students entering the data science field are in a favorable position, with opportunities to enhance their resumes through research, clubs, and relevant coursework. The discussion underscores the importance of practical experience and networking, suggesting that students leverage university resources to secure internships and job placements. Overall, the conversation provides actionable insights for both seasoned professionals and newcomers aiming to succeed in the competitive data science job market.
Show Notes
How to get a data science job
This video is for those of you who are learning data science in the hopes of getting a data science internship or job. Just because you learned data science doesn't mean you will automatically get interviews and land a data science job. There's more to it that I break down in this video :) ______________________________________________________________________Timestamps00:00 Intro01:19 Framework01:34 Transitioning into data science04:31 Students06:22 Summary______________________________________________________________________Links mentioned in videoKen Jee's 66daysofdata (highly recommend for everybody!): https://www.youtube.com/watch?v=qV_AlRwhI3IData science projects for students:https://www.youtube.com/watch?v=2goqyY5XBeIData science projects for non-students:https://www.youtube.com/watch?v=eAgv2-XBIac&t=120s______________________________________________________________________Other videos you might be interested inHow to learn data science in 2021: https://www.youtube.com/watch?v=Axu4tJl8gbMThe resume that got me into FAANG as a data scientist: https://www.youtube.com/watch?v=vx-x-yXXE9I______________________________________________________________________Subscribe: https://www.youtube.com/channel/UC2UXDak6o7rBm23k3Vv5dww/?sub_confirmation=1______________________________________________________________________Real SQL interview question walkthrough series: https://www.youtube.com/watch?v=Td-cmLfQ7uU&list=PLVD3APpfd1tuXrXBWAntLx4tNaONro5dACheck out StrataScratch for SQL interview prep: https://stratascratch.com/?via=tina______________________________________________________________________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 :) I have accepted that I will forever be a lazy person so have since decided to embrace that. My motto is to always minimize effort and maximize outcome!______________________________________________________________________Contactyoutube: youtube comments are by far the best way to get a response from me! linkedin: https://www.linkedin.com/in/tinaw-h/ (second preferred but I might suck at responding)email: [email protected] *If you're reaching out through linkedin or email, please leave a youtube comment just letting me know that you reached out :) ______________________________________________________________________*The StrataScratch affiliate program give me a small portion of the sales price at no cost to you. I'm currently not monetized and really appreciate your support in helping improve this channel! :)#DataScienceProject #DataScienceJob #DataScience #TinaHuang
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.
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Will AI do this in 2026?Tina is a former data scientist at Meta.Her channel focuses on AI, coding, tech, career development, and self-study.Always striving to minimize effort while maximizing outcomes.In fact, she firmly avoids doing extra work to reach her goals - one of the many reasons she loves AI.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.