Founding Applied Scientist

San Francisco, CA - USA

Monthly Salary: Not Disclosed

Posted on: 16 hours ago

Vacancies: 1 Vacancy

Department:

Engineering

Job Summary

Who we are

Koah Labs is building the ad network to power the next generation of AI-native products. Our mission is to help publishers monetize and help advertisers reach the right audience without compromising speed UX or privacy.

Were a small tight-knit team in San Francisco with backgrounds at X Apple and early-stage startups. Weve raised $5.7M from top investors and are growing fast with real traction on both the publisher and advertiser sides.

Working at Koah means joining at the ground floor: youll ship code that shapes the company and the ecosystem were building. We move quickly operate with high trust and care deeply about craft.

Example Projects

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

You might be a fit if

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

If youre interested please send an email to with your full name email address and resume.

Who we areKoah Labs is building the ad network to power the next generation of AI-native products. Our mission is to help publishers monetize and help advertisers reach the right audience without compromising speed UX or privacy.Were a small tight-knit team in San Francisco with backgrounds at X Ap...