About our Data Science teamOur 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 roleAs 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.
