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.
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.
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.
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.
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.
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.
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.
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