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) and Airtable to LLM analyzer
Applicants at any stage in their careers are welcome to apply, including students.