Data Science on Github: How to Get Started Quickly

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SUMMARY

The discussion emphasizes the importance of showcasing coding skills on GitHub for aspiring data scientists and data engineers. Participants agree that while personal repositories can be beneficial, meaningful contributions to established projects often provide a stronger signal to recruiters. It is recommended to focus on issues labeled as "good first issue" or "contributor-friendly" to find accessible projects. This approach not only enhances visibility but also aligns with the interests of potential employers.

PREREQUISITES
  • Understanding of Git and GitHub for version control
  • Familiarity with Python programming language
  • Knowledge of open-source contribution practices
  • Basic concepts of data science and engineering roles
NEXT STEPS
  • Explore GitHub repositories tagged with "good first issue" to identify suitable projects
  • Learn about contributing to open-source projects in Python
  • Research best practices for creating a compelling GitHub profile
  • Study common data science algorithms and implement them in your own projects
USEFUL FOR

Aspiring data scientists, data engineers, and anyone looking to enhance their GitHub presence to attract potential employers.

Avatrin
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Hi

I have the educational background to do a few jobs I have seen posted as "data scientist" or "data engineer". However, I keep getting told that to get a job like that with my background, in mathematics, I need to post code examples on Github. However, I always feel like my ideas are either too basic or too advanced (so, either it won't look good enough for recruiters or it'll take me forever to actually write the code). I thus never get started.

My question is, how good should my code be? Where should I start?
 
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Just put it out there. If you include the link in your resume and job application, they'll look at it and decide if it is what they are looking for in a programmer.
 
Avatrin said:
Hi

I have the educational background to do a few jobs I have seen posted as "data scientist" or "data engineer". However, I keep getting told that to get a job like that with my background, in mathematics, I need to post code examples on Github. However, I always feel like my ideas are either too basic or too advanced (so, either it won't look good enough for recruiters or it'll take me forever to actually write the code). I thus never get started.

My question is, how good should my code be? Where should I start?

I don't think you need to post code examples on GitHub to appeal to your employer. I've gone through thousands of applications and actually, on some 90% of the applications where I've seen it included, it has actually hurt the candidate instead.

If you do go the route of including your GitHub profile, I personally feel that a better signal than your own repositories is to have meaningful contributions to large projects. This also gives you an easy way to generate ideas that are relatable to your recruiters - because surely, if it's an important issue to a large project, it's probably accessible to a wide audience. A way to find these is to look for issues tagged with "good first issue" or "contributor-friendly". Here's a few examples for Python: 1, 2, 3.
 
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