Applied Scientist
Listed by employer · Checked
Older posting · still listed ·
- Work arrangement
- hybrid
- Employment
- FullTime
- Stated compensation
- USD 200,000–300,000 1 YEAR
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Requirements
1 with evidence8 unclear or unstated- Remote policy
- hybrid
“Provider workplace type: hybrid”
From employer posting metadata - Employment type
- FullTime
- Compensation
- USD 200,000–300,000 1 YEAR
8 fields not stated in this posting
- Employer sponsorship
- Not specified
- Geographic scope
- Not specified
- Degree requirement
- Not specified
- Security clearance
- Not mentioned
- Timezone / hours
- Not specified
- Citizenship requirement
- Not mentioned
- Minimum experience (years)
- Not specified
- Work authorization
- Not specified
These details were not stated in the tracked posting. Confirm with the employer.
Original job description
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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: Flutter, React Native, Android, iOS
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
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