Data Product Operations Lead

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.