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Applied Scientist

Koah· Engineering
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Hybrid (San Francisco)$200k - $300kFull-timePosted 3mo ago

About the role

Koah Labs is building an ad network to power AI-native products, seeking an Applied Scientist to tackle challenging problems in real-time bidding, privacy-preserving data analysis, and ad matching, with a hybrid work arrangement in San Francisco.

Responsibilities

  • Design efficient algorithms for real-time bidding systems, building upon the current pricing literature
  • Create and productionize regression models to predict end conversions based on demographic, audience, and semantic data
  • Apply privacy-preserving clustering methods to categorize conversational data to improve advertiser outreach
  • Analyze and pore over data to find alpha that can improve the core ad matching system balancing publisher and advertiser outcomes

Qualifications

  • You have an advanced degree in Physics, Computer Science, Mathematics, Statistics, Engineering, or a related field
  • You enjoy identifying and owning challenging problems, forming testable hypotheses, and conducting impactful research to drive significant business impact
  • You have a relentless focus on continuous learning and making an impact with an ability to question the status quo
  • You have strong mathematical and statistical modeling skills
  • You enjoy communicating conclusions to both technical and non-technical audiences alike

Skills

Required:Advanced degree in relevant fieldAlgorithm design and analysisStatistical modelingResearch and hypothesis testingCommunication
Last updated Aug 9, 2026. Interested? Apply on the company site.
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About Koah

The Ad Network Built for AI | Koah

The Ad Network Built for AI — Native ads powered by real-time intent matching — not borrowed from the last era.

AIadvertisingai-plg-top-20first-party dataintegrationmemorymonetizationnative ads
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