You don’t want to be an average data scientist? Build these 7 Habits

Mar 28, 2024 2:31 pm

Hey there!


Are you looking forward to this Friday more than usual?


I know you so well!


Our habits define our workflow. And, if you want to maintain your competence as a data professional, you have to hone your habits and make them your lifestyle.


Letting go of bad habits and swapping them with good ones is already hard enough. Now you tell me I have to maintain and nourish them?


Yes, but, it’s not that hard after all, and here are 7 habits every data scientist should nourish if they want to be effective and successful in their work


Problem solving mindset:

If you want to be competitive in the industry, identifying problems is not enough. You have to solve them too.


Apply data science methods to solve problems, and do it consistently. You’ll do your best with experimenting and exploring.


Refactor frequently:

As you grow, you’ll become a better coder and a better problem-solver. If you write or used to write a lot of code, make sure to refactor it regularly and search for small things to make things better.


This will train your brain to recognize more effective and efficient solutions and patterns.


Never stop learning

If you choose data science in your career, you have to know your learning never stops.


Whether you’re in academia or in the industry, your expertise will only continue to grow, and by learning new things, you’re becoming a more powerful asset.


Connect and network

The best data scientists know that they’re not the best and they’re always open to learning from those who are better than them.


Join communities, connect with like-minded people in the industry, and learn how you can improve both your hard and soft skills.


Patience and persistence:

Data science projects can be challenging and time-consuming.


Patience and persistence are necessary to troubleshoot issues, refine models, find meaningful insights, and pay off tenfold in data science in particular.


Documentation and reproducibility:

Maintaining clear documentation and ensuring that analyses are reproducible are key habits that contribute to the transparency and credibility of their work.


Begin every project by defining its end goal:

In your initial planning, identify the problem to solve or insight to obtain, and assess the project's feasibility and sustainability.


This roadmap guides your coding and model development, ensuring a clear path to your desired outcome. Make it a habit to start with this strategic vision for efficient and targeted project progress.


Do you still feel stuck? I created a simplistic habit tracker you can download and either use on your devices or print it.


I hope it helps you establish healthy and sustainable habits that you can turn into a new lifestyle!

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Good luck,

Until next time, Danica

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