What I’ve Learned About the Top 1% of Data Scientists

Lately, I’ve been curious about what separates truly exceptional data scientists from everyone else. After some deep thinking and observation, here’s what stood out to me personally:

1. They care about real problems, not just technical ones.
   They focus on business impact—solving problems that truly matter.
2. They don’t rush through data.
   They take their time, exploring and understanding every detail and nuance.
3. They explain things simply.
   They can take something complicated and make it easy for anyone to grasp.
4. They’re strategic thinkers.
   They align their work with broader organizational goals instead of just completing tasks.
5. They test everything rigorously.
   They validate their assumptions rather than guessing or trusting intuition alone.
6. They build models that actually work in the real world.
   Their code and models aren’t just experimental—they can scale in a real production environment.
7. They’re always learning intentionally.
   They regularly invest time in sharpening core skills, not just keeping up with the latest buzzwords.
8. They embrace creativity.
   They’re not afraid to try unconventional solutions or think outside the box.
9. They understand people, not just data.
   They recognize data as reflections of human behaviors and motivations.
10. They prefer simplicity and effectiveness over complexity.
    They choose the simplest solution that gets the job done, instead of complicating things unnecessarily.

Why this matters to me:
I’m pursuing these traits because they align closely with who I aspire to become as an engineer and as a thinker(INTJ).

If you’re on a similar journey, I’d love to hear what resonates most with you