KALW is looking for a skilled developer to work on an audience analytics project for a minimum of 3 months, up to 6.
We are hoping to prototype an AI-powered tool to consolidate audience feedback across all channels (emails, social media, apps, voice memos, etc.) and create a centralized, searchable repository for internal use. All data must remain completely confidential.
Skills needed:
- Using AI bots (Claude Code, ChatGPT or Gemini CoLab) to write, test software across integration boundaries
- Pull content using platform APIs (email, social, podcast ratings) into Airtable using python scripts
- Exporting Airtable content into Google Docs/other format using scripts
- Pushing Google Docs to Notebook LM (or other LLM analyzer) for interface analysis
- Creating this with a weekly monthly automation so that only thing the team is doing is common/shared analysis and discussion/decision-making at meetings
- Design Airtable template(s) to hold KALW feedback data; use a starting template we give you
- Verify/be comfortable with a rough architecture to connect the listening agents (software) to storage (likely Airtable) to LLM analyzer
Applicants at any stage in their careers are welcome to apply, including students.
Please send inquiries to shereen@kalw.org.