What is “sr.cag”?

sr.cag (formerly the Scripps Ranch Commerce Advocacy Group) is an organization originally registered as a California-based 501(c)(3) focused on leveraging data science and machine-learning tools to support public-sector improvement and local service-sector growth.

In 2023 and 2024, sr.cag operated similarly to a localized chamber of commerce. We conducted internal analytics projects and used our findings to provide data-driven policy recommendations and strategic guidance to the small business community in San Diego, California. During this period, we also hosted networking events to help business owners interpret our insights and apply them to fuel their growth.

The organization paused activity during the first half of 2025 as we began shifting toward a more scalable, partnership-driven, and revenue-sustaining model. Moving forward, sr.cag aims to expand nationally, broaden its scope beyond small businesses, and provide predictive analytics support for service-focused nonprofits and local political campaigns, as well. This strategic pivot is rooted in our commitment to helping address systemic issues such as homelessness, food insecurity, and housing instability: areas rich with public data but historically underserved by applied analytics.

What sets sr.cag apart from other data science organizations is our willingness to translate quantitative findings into actionable civic advocacy. When our analyses demonstrate statistically significant results, we summarize them into publishable briefs for local, state, and federal lawmakers. In doing so, we seek to drive meaningful policy change using the power of numbers, while also building scalable analytics solutions that can be deployed by organizations of any size.

Over-simplified organization pipeline

Why am I seeing this advertisement as a student?

sr.cag is currently on the hunt for student talent (both undergraduate and graduate) to support a diverse range of roles across communications/media, public policy, and data engineering as we initiate 2–3 defined projects beginning January 2026.

Students are often the most motivated to solve problems in their communities, and the time commitment required for these projects can fit seamlessly within a student’s busy academic schedule. We are looking for students from a variety of majors and backgrounds, with an emphasis on UC San Diego and Carnegie Mellon University students due to proximity and campus partnerships. These projects are designed to be collaborative, resume-ready, and directly tied to community impact. Participants will have the chance to work alongside faculty mentors, local policymakers, and nonprofit leaders while gaining practical experience that translates beyond the classroom. No prior industry experience is required: just curiosity, reliability, and a willingness to build something meaningful.

This is a great opportunity to get (an) impactful project(s) in your portfolio while contributing to data-driven solutions that support real organizations and real people in need.

Is it paid?

Positions beginning January 2026 will be on a flexible, volunteer basis. However, due to generous grant funding we’ve received + our grant application process, Stipend positions may be available later in the year.

What positions are you looking to fill?

We are looking to fill the following positions. There is no required major(s) for each position, but we have provided recommended skills/areas of study below

Data Engineer Volunteer (grad/undergrad)

Recommended tools/skillset: Python (Pandas, NumPy), SQL, data cleaning/preprocessing, familiarity with APIs, optional experience with geospatial libraries (e.g., GeoPandas, Folium), version control (Git), GIS/Spatial analysis
Recommended majors/programs: Data Science, Computer Science, Statistics, Informatics, Computational Social Science, Applied Mathematics, Information Systems

Communications & Media Volunteer (grad/undergrad)

Recommended tools/skillset: Strong writing skills, Canva or Adobe Suite proficiency, social media content planning, basic copywriting, analytics familiarity (Instagram/Twitter/LinkedIn insights), optional video editing
Recommended majors: Communications, Media Studies, Marketing, Journalism, Public Relations, Digital Strategy

Public Policy & Grant Administration Volunteer (grad/undergrad)

Required tools/skillset: Professional writing, legislative analysis, grant discovery and drafting, Excel/Sheets, attention to detail, good communication skills, optional Tableau/ArcGIS familiarity
Recommended majors: Public Policy, Political Science, Economics, Law & Society, Public Administration, Urban Studies

Outreach Volunteer (grad/undergrad)

Required tools/skillset: Strong interpersonal communication, public speaking experience, event coordination, community engagement, professional email etiquette, stakeholder note-taking, optional cold outreach experience
Recommended majors: Sociology, Political Science, Public Relations, Business Administration, Psychology, Community Health Sciences, Urban Studies

What’s the time commitment?

3 hour minimum per week; most volunteers in the past have contributed on-average 3–5 hours per week. If you’d like to take on more tasks, you are welcome to speak with Mehri.

What projects could I contribute to in 2026?

Some of our 2026 pilot projects include:

• Vehicle Break-In Risk Model — A predictive analytics model designed to forecast the likelihood of vehicle break-ins across neighborhoods by week or month. Using publicly available data such as police reports, 311 streetlight outage data, and nightlife density, this project explores temporal and environmental patterns to identify high-risk zones and inform local prevention efforts.
• Overdose Factor Analysis Project — A multi-state data study aimed at identifying the most significant socioeconomic and environmental factors driving overdose trends across Pennsylvania and California. By combining county-level public health data with demographic and infrastructure indicators, this project helps highlight where prevention and resource deployment can be most effective.
• Donor Data Predictive Tool — A machine learning project that models donor behavior for community or political campaigns, using features like donation frequency, amount history, and geographic indicators. The model will inform outreach strategies and generate actionable insights through an interactive analytics dashboard hosted on sr.cag’s website.

If you are applying to be a Data Science Volunteer, you will have the opportunity to rank these projects from most to least interested. Most volunteers focus on 1–2 projects. If you are applying to be any other volunteer, your role will not be specialized to a certain project.