Data Science Evangelist

Data Science Evangelist

About Coiled

Coiled connects data scientists and researchers to distributed infrastructure using the Python data science stack (Numpy, Pandas, Scikit-Learn, etc) and Dask, a popular open source library for parallel analytics. We come from the open source Python community, and are long-time maintainers of this stack in general and Dask in particular. We’re building a product that enables organizations and enterprises to collaborate better using Dask by solving the setup, scaling and security challenges of the standard open source Python stack.

Through Dask, we enable analysts and scientists to understand the effects of climate change, fight cancer, and play the stock market. We have a wide range of customers solving these problems who need to deploy Dask throughout their organization to enable data science teams. This is a challenging task, and doing it well requires attention to user experience, and building distributed infrastructure which is robust, secure, and observable.

The Role

There is a large community of expert developers and institutions using Dask today. However the barrier to entry for new users can be high, especially in domains without deep programming experience. Your job will be to lower this barrier to entry in a variety of ways:

1. Build examples and blogposts showing how to solve common problems
2. Engage in conversations on GitHub, Slack, and in user community meetups
3. Communicate with developer and marketing teams to help prioritize company direction
4. Listen, and engage in user empathy

To do so, you will also explore new avenues for growth, building and harnessing communities in novel spaces (such as Quora, reddit, Kaggle, newsletters, and more). In addition, you will touch many parts of Coiled, including product development, so that you’re in touch with our product, our market, and our communities.

You will also play a pivotal role in connecting the Dask and Coiled communities by understanding the pain points of the former and building educational data science content around how we’re solving for these at Coiled.

You will grow your skills as a data scientist / software engineer by engaging with a wide variety of problems. You will grow your communication and writing skills by communicating the lessons that you learn on the job.

Ideally you will be able to:

    • Solve data science problems with the Python software stack
    • Write professional blogposts
    • Speak publicly
    • Fix the occasional bug report
    • Listen and convey empathy to a wide variety of humans
    • Additionally one or more of the following specialties will help you stand out:
    • Successfully organized and cultivated large community events
    • A successful career as a data scientist
    • Experience running a successful blog

    • Please keep in mind that we are describing the background we imagine would best fit the role. Even if you don’t meet all of the requirements, yet you are confident that you are up for the task, we absolutely want to get to know you!

More About Us
Coiled is a remote-first company. We support you living and working from where you feel fulfilled, providing that you can collaborate effectively with your team.

Our Mission
Increase access to scalable computing in three ways:
1: Coiled Cloud, managed one-click Dask deployments for everyone
2: Coiled Enterprise, support and training for scalable Python and Dask
3: Community Outreach, with continued support of open source software

Our Values
Accessibility — we make computing accessible to everyone, from the largest organizations to individual students and researchers around the world
Openness — we communicate openly and honestly about what we can and can’t do, following our roots in community driven software
Mission Driven — we care about making a difference in our world

Coiled is an Equal Opportunity Employer and encourages people of all backgrounds, identities, and abilities to apply. We are committed to being a consciously inclusive place to work, valuing all ideas and perspectives.
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