13 Ideas to Build Your Data Science Brand — Part 1

How do you stand out from the rest of the data professionals?

We are all trying to establish ourselves and stand out in the ever-competitive data science ecosystem. I have been somewhat successful in navigating this space and want to share the opportunities I pursued that helped me build my brand. You should approach each of these opportunities with humility, honesty, and seek to forge long-lasting and mutually beneficial relationships with others you meet. Most importantly, be your most authentic self.

1. Attend Conferences

This is an awesome time to network with other data enthusiasts and get a glimpse of what is popular within the data community. PyData and PyCon are two of the best conferences. If you can’t afford to attend, apply for scholarships or grants. Most conferences offer some sort of financial aid such as academic discounts or “pay what you can.” To gain the most out of this experience while attending, you should:

a) Participate in open source sprints to meet and build relationships with core contributors and maintainers of major projects.

b) Give a lightning talk. Spend 5 minutes describing a project you’re passionate about.

c) At lunch, sit at a table with people you don’t know and share data war stories.

d) Be fully present in talks and at the end ask meaningful questions.

e) Speak with speakers after their talks.

2. Volunteer at Conferences

A major upside of volunteering is that you may receive free or discounted admission. You’ll get to understand the inner workings of a conference and build long-lasting relationships with the organization staff that is responsible for hosting these events. You’ll also get the opportunity to meet high-profile speakers in a low-stress environment.

3. Give Talks at Local Meetups

This is your chance to build up your confidence speaking in front of others. You don’t need a complex topic, just a simple explanation of a data tool or novel concept.

4. Join a Research Lab

Organizations like District Data Labs, offer opportunities called ‘research labs’ that allow participants to spend a semester researching a specific machine learning topic with a group of like-minded individuals

5. Contribute to Open Source Software

This is a great opportunity to build your software development skills beyond data wrangling and analysis. You will learn how to build a maintainable project and all the auxiliary processes required in making it successful. Try working on smaller projects like Yellowbrick where you can make frequent and meaningful contributions that can potentially lead to you becoming a core contributor or maintainer.

6. Attend Hackathons

This is a good place to test your skills out in the wild and be creative. Be sure to add your any achievements to your LinkedIn profile.

7. Join Committees

A few examples would be the PyCon poster committee (PyCon has numerous others), the Small Development Grants program from NumFocus, or NumFocus’ affiliated project selection committee. This is a great way to fill your network with hard-working people that play a significant role in supporting the data science ecosystem.

Part 2 — Can be found here

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