Data Scientist
- Salary
- $155K - $220K
- Level
- Mid
- Work type
- On-site · San Francisco
Not stated in the posting: visa.
Open. First seen 3 November 2026.
About the role
About David AI
David AI's standard text
David AI is the first audio data research company. We bring an R&D approach to data–developing datasets with the same rigor AI labs bring to models. Our mission is to bring AI into the real world, and we believe audio is the gateway. Speech is versatile, accessible, and human—it fits naturally into everyday life. As audio AI advances and new use cases emerge, high-quality training data is the bottleneck. This is where David AI comes in.
David AI was founded in 2024 by a team of former Scale AI engineers and operators. In less than a year, we’ve brought on most FAANG companies and AI labs as customers. We recently raised a $50M Series B from Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, First Round Capital and other Tier 1 investors.
David AI's standard text
Our team is sharp, humble, ambitious, and tight-knit. We’re looking for the best research, engineering, product, and operations minds to join us on our mission to push the frontier of audio AI.
About our Data Science team
Our Data Science team turns the activity across our business into the insights, metrics, and data foundations that guide how we grow. We move fast, own our work end-to-end, and partner closely with product, engineering, research, operations, and go-to-market to make sure the company is working on the right problems, measuring what matters, and drawing data backed conclusions.
About this role
As a Data Scientist at David AI, you'll turn our data into decisions. You'll help figure out what we should be building, measure whether it's working, and lay the foundation for how the company defines, stores, and trusts its data.
In this role, you will
- Work cross-functionally to identify the highest-leverage business problems and drive them to resolution.
- Form and advocate your own point of view on what you and the broader team should prioritize, using data to shape the roadmap.
- Define core metrics that measure the health of our business, products, and operations, and own the data dictionary that keeps them consistent across the company.
- Own A/B experimentation end-to-end, from hypothesis and test design to analysis and ship decision.
- Design and build reliable ETL pipelines and data models that make our data trustworthy, well-documented, and easy to use.
- Work across the full range of data science, including experimentation, deep-dive analysis, forecasting, dashboards, and modeling.
Your background looks like
- 3+ years of experience working on a cross-functional team as a product Data Scientist.
- Experience turning ambiguous problems into clear recommendations.
- Experience working in a fast paced environment where you owned your work end-to-end.
- Proficiency with AI coding tools and agentic workflows, grounded in the SQL and Python skills needed to validate their output.
Bonus points if you have
- Hands-on experience building and maintaining ETL pipelines and data models (e.g., dbt, Airflow, Dagster).
- Experience defining company-wide metrics, building a data dictionary, or setting up analytics governance.
- Experience with audio data, data research companies, or LALM evaluations.
What this role asks for
Standard for data science / ML roles
Python
Common in data science / ML postings at any company.
78% of this description is written for the role. The rest is David AI's standard text, folded away below.
Compared with David AI's other open jobs.
The team: Operations
This role is one of 3 open in Operations. 3 were posted in the last 30 days.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Python (2 of 3)
OTHER ROLES ON THIS TEAM
- Audio Engineer posted Nov 2
- Head of Quality Assurance Operations posted Oct 7
From the team and dates on David AI's own job board.
Salary context
73 other open postings titled Data Scientist state a salary: median USD 135,000 to USD 195,050 a year.
See Data Scientist salaries in San Francisco →
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