Thanks for stopping by!
The Data Science Working Group’s purpose is to efficiently assess, inspire, and tackle Code for San Francisco’s data science needs, as well as to help the City with its data science needs whenever appropriate. Our practicing and aspiring data scientists are available to:
- develop data science-centric solutions to social good problems;
- assess/inspire the possibility of data science components in other projects;
- provide resources to help produce those components;
- provide a learning environment for ourselves and others to learn more practical data science.
In pursuing the above, we humbly hope that CfSF's dedicated project groups come to consider us an integral and synergistic resource for the brigade at large.
Team Leads: Rocio Ng, Ph.D. and Vincent La
Wiki (resources): DSWG Wiki
Group Email Contact: datascience[at]codeforsanfrancisco.org If you are interested in volunteering to generallhy help the group as a whole outside of project please reach out to one of the team leads.
Here's what we're currently working on, mostly with gov't/org partners, but as mentioned above, we're also eager to work with -or inspire- dedicated project groups.
We also have a number of new projects that will be launched in the coming months!
Projects On Hold
The following are in need of new project leads and contributing members. Please check them out and reach out to DSWG team leads if you are interested in reviving one of these projects!
- SF OpenData Search Analytics for Improving UX
- CTA-NorCal Homeless Program Outcomes Analysis
- Interactive visualization of SF's building emissions and energy use
- The Science of Housing: Impact of Planning Policy on the Housing Crisis
- Small Business Association
- Friends of the Urban Forest: Analyses and Visualizations
- CA Dept. of Justice OpenJustice Hypothesis Testing and Predictive Modeling
- U.S. Dept. of Transportation Hazmat Incident Prediction and Anomaly Detection
- City of SF 311 Case Data Analysis
- City of SF Budget Visualization
- U.S. Dept. of Transportation Traffic Fatality Analyses