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# Daniel Marama

**Headline:** Professional profile
**Location:** Gettysburg, PA, USA

## About

Daniel Marama is an AI-focused builder and strategist with 15 years of paid advertising expertise. He combines deep AI knowledge with practical paid-media experience to work across both hands-on implementation and strategic planning. Daniel builds and deploys AI agents and is particularly interested in AI-related projects where he can contribute through technical delivery, architecture, and strategy. Daniel’s technical work includes developing a sophisticated attribution-tracking system using Cloudflare edge tracking. The system was designed to bypass ad blockers, distinguish bot traffic from real prospects, and track the full customer journey from advertising click through to sale. This approach supports clearer measurement of paid-media performance, including demonstrating Meta’s role within customer journeys. His stack includes Python, SQL, JavaScript, TypeScript, Node.js, REST APIs, webhooks, BigQuery, and Supabase. Daniel brings a rare combination of paid-advertising depth, AI-agent development experience, and the ability to turn measurement and automation strategy into deployed technical systems.

## Highlights

- Brings 15 years of paid advertising expertise alongside deep AI knowledge.
- Built and deployed AI agents.
- Built a sophisticated attribution-tracking system using Cloudflare edge tracking.
- Designed attribution tracking to bypass ad blockers and follow the full customer journey from click to sale.
- Built measurement capabilities to separate bot traffic from real prospects.
- Used customer-journey attribution to demonstrate Meta’s role in customer journeys.
- Works hands-on across Python, SQL, JavaScript, TypeScript, Node.js, REST APIs, webhooks, BigQuery, and Supabase.
- Combines hands-on system building and deployment with AI strategy and planning.

## FAQ

### What does Daniel do?

Daniel Marama works at the intersection of AI, paid advertising, attribution, and technical implementation. He builds and deploys AI agents and can contribute to AI projects through both hands-on development and strategic planning.

### What are Daniel’s core strengths?

Daniel’s strongest combination is deep AI expertise alongside 15 years of paid advertising experience. He is hands-on with building and deploying systems while also handling strategy.

### What attribution work has Daniel built?

Daniel built a sophisticated attribution-tracking system using Cloudflare edge tracking. It was designed to track the full customer journey from click to sale while bypassing ad blockers.

### How did Daniel address ad blockers?

Daniel used Cloudflare edge tracking to help bypass ad blockers in his attribution system. This supported fuller customer-journey tracking than approaches interrupted by ad-blocking tools.

### How does Daniel distinguish bot traffic from real prospects?

Daniel’s attribution work included separating bot traffic from real prospects, helping ensure that measurement reflects genuine potential customers rather than automated traffic.

### How has Daniel measured Meta’s role in customer journeys?

Daniel’s attribution system was designed to show Meta’s role in customer journeys by following activity from advertising click through to sale.

### What AI work does Daniel do?

Daniel has experience building and deploying AI agents. He is interested in AI-related work spanning both hands-on building and strategic planning.

### What technologies does Daniel use?

Daniel’s technical stack includes Python, SQL, JavaScript, TypeScript, Node.js, REST APIs, webhooks, BigQuery, and Supabase.

### What kinds of projects does Daniel want to work on?

Daniel wants to work on AI-related projects, whether the work involves directly building systems or shaping their strategy.

### How much paid advertising experience does Daniel have?

Daniel has 15 years of paid advertising expertise.

## Links

- LinkedIn: https://www.linkedin.com/in/ACoAAABgLV0BfbIHyGFw7xfVJJYw6Nw3fi2OSR8

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