[New Data Science Task] Onboard to Analytics Measurement Plan

[oscarsyu]

Context

This is a onboarding task for your first 2-week sprint (or "iteration") as part of DataSF! We're excited to have you and are looking forward to the impact you'll make on the team.

Your role here as a data scientist is to:

• find datasets and ingest them in a scalable manner
• use data to inform product experience
• understand what data is available and what we present as part of the product
• build exciting prototypes with cutting edge tech

We're looking to you to drive vision and ideas, so don't feel like you "need" to stay within your lane, but hopefully this should help you get started on some tasks.

The goal is to ultimately get familiar with the project and begin contributing to the Measurement Plan, and PostHog analytics platform

Definition of Done

By the end of this period you should:

• understand what SafeHome is
• know who to chat with
• start contributing to the project

Details

• Understand the project
  1. Explore https://www.safehome.report/, try inputting some addresses and play with the site. We'd love your feedback & ideas!
  2. Make sure you take a detailed look at the Roadmap to understand what are the project's current priorities
  3. Join the #proj-earthquake-datasci channel, and read through some of the more recent (1-2 weeks ish) of messages
  4. Visit the SafeHome Canvas, familiarize yourself with the Google Drive, Github, Product Requirement Document. These represent our "best attempt" at capturing the current state of the project. Please also familiarize yourself wtih the SafeHome Github project board. This is where we keep track of the tasks you are assigned to for each iteration.- Understand the data & tech stack
  5. We have a strong preference for Python and Co-Lab for analysis, but please use the appropriate tool for your application.
  6. Navigate to the "tech stack" resource in the Canvas to better understand the stack we use for our project too.
  7. "Core Datasets"
     • https://data.sfgov.org/Housing-and-Buildings/Soft-Story-Properties/beah-shgi/about_data
     • https://data.sfgov.org/Geographic-Locations-and-Boundaries/Soil-Liquefaction-Hazard-Zone/i4t7-35u3/about_data
     • https://www.conservation.ca.gov/cgs/tsunami/maps
• Learn Skills
  1. We encourage this to a space where you get to learn new skills and explore! Highly suggest leveraging the internet, online courses, and other team members for learning & advice.
  2. We're still in progress in building more resources in-house, but you can take look at some of the stuff we have today:
     • [Product Analytics 101](https://docs.google.com/document/d/19ZWZZOtMj6BWFiQ9iAltAlL_KVHEtV6XZ8kBh3ni6j4/edit?tab=t.0#heading=h.auvnxplsw8t\)
• Meet People
  1. Make sure you meet some of the folks you'll work with. At a minimum:
     1. Oscar Syu (asst. project lead/Data science lead)
     2. For Data Eng/ML:
        • introduce yourself to Backend/Frontend eng: esp Anna Gennadinik, Svetlana Eliseeva
     3. For Data Products/Analytics
     • introduce yourself to Design/UX: esp Ramya Rajasekaran
     • recommend introducing to the above Backend/Frontend folks if you have time too
  2. This is just a suggested starter list, please reach out to more if you are able to!
• Take on a starter task! Talk to Oscar about getting on one.