Data Scientist
Koahlabs
| Company | Koahlabs |
| Category | Data & Analytics |
| Location | San Francisco |
| Remote | Hybrid |
| Employment | Not stated |
| Level | Not stated |
| Salary | USD 180k–250k |
| Posted | 22 Jan 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
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
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