/data-science-h4la

The Hack For LA Data Science team is a Community of Practice within the LA brigade seeking to make analytical and machine learning services available to local communities and organizations.

Primary LanguageJupyter Notebook

Data Science Community of Practice

Welcome to the Data Science Community of Practice. We are happy you are here!

Let's get Started

If you have not read the Guide for New Volunteers, please do so.

  1. Join the #data-science Slack channel and introduce yourself.
  2. Slack one of our Data Science Community of Practice leads Ryan or Sophia with your Gmail address.
  3. Accept your Google Drive invite to access the shared folder.
  4. Add yourself to the Team Roster and inform Ryan or Sophia after you have done so.
  5. Join our meetings Thursday at 8 pm PST via Zoom.
  6. Check out the open Data Science roles we have available.

The Data Science Community of Practice is one of many. See all our Communities of Practices

Focus

The Hack For LA Data Science team is a group within the LA brigade seeking to make analytical and machine learning services available to local communities and organizations. We have three main goals as a team:

  1. To provide data science services to communities in the Los Angeles area. Please contact us if you have a proposal for a data science project. We have many talented data scientists with track records in industry and academia, and we are excited to be able to support our communities.

  2. To provide mentorship and development opportunities for junior data scientists in the LA area. We aim to connect new data scientists with projects that match and advance their skill levels, as well as provide opportunities to learn new technologies and make connections with programmers in the Los Angeles area.

  3. To provide support and guidance on data science problems for teams within the Hack For LA organization. We stagger our meetings between project work and open support meetings, where we invite project members within Hack For LA to get advice on challenges related to machine learning, data visualization and data engineering.

Roles: Data Scientist; Analyst; Data Engineer; Machine Learning Engineer; Data Visualization Specialist

Languages

  • Python
  • JavaScript
  • R
  • SQL
  • Shell/BASH