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SkillsCast

Creating a Strong Data Science Portfolio

24th June 2019 in London at CodeNode

This SkillsCast was filmed at Keynote by Emily Robinson on Creating a Strong Data Science Portfolio

As data science explodes in popularity, more and more people are vying for entry-level data science jobs. How can you stand out from the crowd? If you're a junior or mid-level data scientist, how can you continue to grow your skills, meet other data scientists, and share what you've learned?

In this talk, Emily will show you how you can make a strong data science portfolio, including by giving talks, contributing to other's open source projects, writing tutorials, and building side projects, that will accelerate your career.

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Thanks to our sponsors

Creating a Strong Data Science Portfolio

Emily Robinson

Emily is a data scientist at DataCamp, where she's built their A/B testing analytics system and analyzed over 100 experiments. Previously, she worked at Etsy as a data scientist where she worked with their search team to design, implement, and analyze experiments on the ranking algorithms, UI changes, and new features.

SkillsCast

As data science explodes in popularity, more and more people are vying for entry-level data science jobs. How can you stand out from the crowd? If you're a junior or mid-level data scientist, how can you continue to grow your skills, meet other data scientists, and share what you've learned?

In this talk, Emily will show you how you can make a strong data science portfolio, including by giving talks, contributing to other's open source projects, writing tutorials, and building side projects, that will accelerate your career.

YOU MAY ALSO LIKE:

Thanks to our sponsors

About the Speaker

Creating a Strong Data Science Portfolio

Emily Robinson

Emily is a data scientist at DataCamp, where she's built their A/B testing analytics system and analyzed over 100 experiments. Previously, she worked at Etsy as a data scientist where she worked with their search team to design, implement, and analyze experiments on the ranking algorithms, UI changes, and new features.