Data Scientist
koahlabs
San Francisco
Posted Jan 22, 2026
$180,000–$250,000 per year
- Full-time
- Remote
- Engineering
Job description
**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. We’re a small, tight-knit team in San Francisco with backgrounds at X, Apple, Meta, and early-stage startups. We’ve raised 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: you’ll ship code that shapes the company and the ecosystem we’re building. We move quickly, operate with high trust, and care deeply about craft. **Our Stack** - **Infra**: Terraform, AWS, LGTM (Loki, Grafana, Tempo, Mimir), Tailscale, Cloudflare - **Data**: PostgreSQL, ClickHouse, Redis, Kafka, Python - **Core Application**: Ruby on Rails, React, TypeScript - **SDKs**: iOS, Android, Web, Flutter, React Native **In this role, you will** - Sit within product engineering and help drive product decisions using data and causal reasoning - Design, implement, execute experiments and analyze results - Help level-up all of engineering, encouraging data driven decisions and a deep understanding of the important metrics that drive our business forward - Use rigorous statistical thinking and hands-on modeling to turn our rich marketplace data into tools that directly shape product decisions and key insights **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