# Data Product Operations Lead

**Company:** [David AI](https://hotfix.jobs/companies/david-ai)
**Location:** San Francisco, CA, New York, NY
**Role:** Product Operations
**Salary:** $125k – $180k/yr
**Experience:** 1+ years
**Skills:** Data Pipelines, audio data processing, ml operations, Cross-Functional Leadership, metrics-driven optimization, System Design, product intuition
**Posted:** 2026-07-22

> Lead end-to-end data pipelines at David AI, turning raw audio into high-quality training datasets for frontier AI labs. Own prototypes to scaled production, collaborating with researchers, engineers, and ops teams while driving metrics on throughput, quality, and cost.

## Job Description

## Responsibilities
- Own end-to-end success of a data pipeline, from early experiments to scaling up production systems that generate high-quality audio data at high volumes.
- Design and run pipelines that process a high volume of audio data with reliability, quality, and efficiency.
- Work with researchers at leading AI labs to identify new model capabilities and turn them into concrete data workflows and project plans.
- Lead cross-functional workstreams across Ops, Product, and Engineering to build scalable “data factory” systems.
- Monitor and improve pipeline health, spotting and fixing issues in sourcing, quality, or process.
- Drive impact with metrics, using throughput, quality, and cost to prioritize and improve.
- Take full-stack accountability across operations, product, engineering, and customers, solving bottlenecks and ensuring delivery.

## Requirements
- 1–6 years in high-intensity environments (e.g. founder, strategy consulting, or venture-backed ops).
- Background in strategy consulting, strategic projects, investment banking, operations, computer science, or similar.
- Systems thinker who can spot leverage points and design for scale and durability.
- Strong product intuition, able to work with engineers and researchers to get to the right answer fast.
- High-execution operator: fast, detail-oriented, and uncompromising on quality.
- Collaborative and low-ego, willing to roll up your sleeves.

## Nice-to-Haves
- A track record of extreme ownership, caring about outcomes over tasks.
- Experience in data, ML, or large-scale operations.

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