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Franklin Dickinson
Senior Data Scientist specializing in product analytics and applied AI
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About
Product data scientist at Meta who also built Fogo, a personal finance app, as a solo developer with a React/FastAPI/Postgres stack and sophisticated LLM evaluation infrastructure. Particularly strong in AI backend quality systems, experimentation, and production decision-making around model cost, latency, and reliability.
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Key Strengths
- Built a personal finance app end-to-end as a solo developer
- Designed a two-layer LLM evaluation harness for deterministic and behavioral quality checks
- Strong AI reliability mindset with gating metrics, observability, provenance, and versioning
- Makes pragmatic backend tradeoffs across reliability, latency, scalability, and developer velocity
- Implemented async ingestion and classification architecture using queues and workers
- Quantified model tradeoffs across cost, quality, latency, and access for production decisions
- Applied ML/LLM systems thinking with caching and secondary-model verification
- Owned incident diagnosis and prevention using dimension-level evaluation signals
- Built A/B testing measurement infrastructure at Meta
- Drove cross-functional experimentation that produced statistically significant retention gains
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