I’m beyond excited!
Today, I bring you the very first episode of a new series I’m starting where I'll be 🎙️ interviewing Data Scientists at various stages of their careers, sharing their journeys to bring YOU fresh perspectives and insights
In this episode, I share my conversation with my friend
, the author of , where we talk about how she broke into Data Science without a traditional background, among other interesting topics.I think you’ll really enjoy it :)
Key Takeaways
Here are some key takeaways from my chat with Mandy:
Breaking into Data Science: "You're more qualified than you think you are." Don’t let a non-traditional background hold you back. Focus on mastering key skills like SQL, Python, and statistics—those are the foundation.
Mentorship: "You own your own growth." While a mentor can provide guidance, it’s on you to take charge of your learning. Show proactiveness by driving the agenda and submitting work for feedback.
Avoid Tutorial Hell: "Start a project from day one." Don’t get stuck in endless tutorials. Even if you don’t feel ready, dive into real-world projects. You’ll learn faster by doing and figuring things out as you go.
Rebranding for Career Switching: "Add a summary at the top of your resume." If you’re transitioning from another field, make it clear in your resume. Focus on showcasing the skills relevant to data science and state your career goal upfront.
Take Smaller Steps First: "Get that job first, then think about what you can do later." Don’t stress if your first role isn’t at a big-name company. Gain experience wherever you can, then use that to move toward your bigger goals.
Communication is Key: "It's not what you can do, but how you communicate what you can do." Technical skills matter, but your ability to explain your work clearly to others, especially non-technical stakeholders, is equally important.
Mock Interviews Matter: "I did 11 mock interviews with friends." Preparation goes beyond just coding. Practice explaining your work out loud, and simulating real interview situations to build confidence.
Develop Product Sense: "Think like a product manager." In product data science roles, understanding the product is just as important as technical expertise. Train yourself to think from the perspective of the product and user.
Networking Through Alumni: "I reached out to alumni from my school." Utilize your alumni network or other industry connections for specific advice on breaking into companies or industries. Personal connections can open doors.
Focus on Resume, Not Just Portfolio: "Forget about the bells and whistles." Before worrying about building a GitHub or portfolio, make sure your resume is solid. Recruiters and hiring managers won’t dive into extra material unless your resume stands out first.
Thank you for reading! I hope you enjoyed this first episode because there are more coming in the future.
See you next week!
- Andres
Before you go, please hit the like ❤️ button at the bottom of this email to help support me. It truly makes a difference!
Breaking Into Data Science Without a Traditional Background | Mandy Liu (Data Scientist, ex-Meta, Smarter Techies) | Ep. 1