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The Only Guaranteed 'No' is the Application You Don't Send
Sometimes it pays to be slightly delusional.
Marina Wyss
January 16, 2025
Welcome to Gratitude Driven, a weekly newsletter where I share practical ideas and insights across personal growth, professional development, and the world of AI and data science.
In This Newsletter
The Only Guaranteed 'No' is the Application You Don't Send
Last week during a mentoring session, someone asked about jobs requiring a certain number of years of experience, and whether they had strong enough skills to apply to big tech companies (or if they should focus on smaller companies when breaking into the field).
I totally empathize with where this is coming from. Job posts can be super intimidating, with long lists of requirements - from a ton of experience to every tool under the sun to PhDs.
The thing is, most of these "requirements" are wish lists, not hard rules. In my mentoring practice I've seen people with two years of experience land Senior roles. I've watched newcomers join FAANG companies. And on the flip side, I've also met MLEs and Data Scientists at top firms who are, let’s just say, not as intimidating as you might imagine…
I think the secret is to have a healthy dose of selective delusion. Those that were successful looked at that intimidating job post and thought "yeah, I could do that" - and then they actually applied.
It’s important to keep things in context. Really, what's the worst that happens if you apply? They ghost you or say no? That's exactly where you are right now by not applying! But there's also a small but real chance they'll say yes. Hiring managers often care more about your potential, learning ability, and enthusiasm than checking every box on their wish list. I know, because I have been hired for “potential” more than once.
So yes, you'll probably get a lot of rejections. That's normal. But remember - every successful person you admire has a folder full of rejection letters somewhere. The only guaranteed way to not get the job is to not apply at all. Let the employers decide if you're qualified - don't eliminate yourself before the game even starts.
(Of course, be reasonable - if you're just starting out, maybe don't apply for Principal ML Engineer positions. But for most roles, it can’t hurt to give it a shot).
If you’d like help crafting your application strategy, I offer 1:1 coaching sessions where we can:
Review your resume and portfolio to highlight your strengths
Develop a targeted job search strategy
Create an interview prep plan and/or practice, coding, behavioral and technical interviews
Map out a skill development roadmap
Book a session with me here, and let's get you that dream job you might think is out of reach!
Start Living Your Ideal Life, Now
Take a minute to picture your ideal life. You’ve got your dream job, financial security, fulfilling relationships, health—whatever matters most to you.
Now, think about the version of you who is living that life. What’s their daily routine? Are they more disciplined, more focused, more intentional with their time? Maybe they eat better, move more, spend less time on distractions, or approach challenges with a clearer mindset.
That version of you isn’t a different person—it’s just you with different habits and priorities.
You don’t have to wait to "become" that person. You can start acting like them right now. If future you is organized, set up a system today. If they value fitness, start a program today.
Success doesn’t drop into your lap; it’s something you build step-by-step. If you start closing the gap now, it’s only a matter of time before that ideal version of your life feels a lot less out of reach.
All Machine Learning Beginner Mistakes explained in 17 Min
I really enjoyed this video from Infinite Codes on beginner ML mistakes. Definitely check it out if you’re new to the field!
Want to chat 1:1? Book time with me here.
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