Joining the Data Science Community

There's benefits to being a positive community member:

• Gain skills
• Grow your network
• Gain opportunities
• Give back

Grow Your Portfolio

Don't stop adding to your portfolio. While you may slow down while employed, it can open you up to other opportunities.

Blog Posts

Writing mini essays helps you solidify your learning. You're at a prime position to teach others who are a few steps behind you on their data science journey.

Projects

These are more time consuming than blog posts, but do them every once in a while. You need to be able to show your technical skills to future employers (and learn about things that are interesting to you that you don't get to do on the job).

Attend Conferences

There's a ton of conferences to choose from. Here's a few axes to consider:

• Academic vs Industrial
• Size
• Hiring Companies
• Level of talks
• Diversity and inclusivity
• Specialty
  Check reviews for conferences and any speakers they have listed. You can network and learn new subjects that could help you on projects at work. See if your employer will pay for these. If you need to make a case for why you should go, here's things to focus on:
• Recruiting. It's hard to find good data scientists. You put the company's name out there as a representative.
• Knowledge. Show that what you'll will be applicable to your current projects or job. Better yet - promise to teach the rest of the team as well.

Give Talks

Find opportunities at conferences with calls for proposals (CFPs). Select conferences to apply for with similar criteria that you would use to select a conference to attend. Think about who you were three months, six months, or a year ago. What do you know now that you wish you knew then?
Another great way to start giving talks is to speak at local meetups.

Prep

• Time yourself
• Practice doing the presentation in front of another human
• Reuse talks!

Contribute to Open Source

Contribute to Other People's Work

Make sure to read any documentation or code of conduct on how to contribute.

• Add to documentation
• Fix beginner-friendly bugs

Make Your Own Package or Library

When you find yourself copying functions between projects or messaging them to your co-workers, it may be time to make a package or library. You'll have to be very thorough on making the code robust. You can market your work via your blog or social media.

Recognizing and Avoiding Burnout

Take care of yourself. Life is more than just data science.

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