Data & Product Operations Lead

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Talentpluto
Published
May 18, 2026
Location
New York, NY

Data & Product Operations Lead: our view in 3 lines...

  • The Role: A cross-functional operations lead who will manage and deliver complex voice and audio data projects for machine learning teams.
  • The Person: The person will own end-to-end execution of voice and audio data projects, coordinate cross-functional teams, ensure data quality and delivery milestones, and identify process improvements and automation opportunities.
  • Requirements: The role requires 2+ years of experience in consulting, strategy & operations or similar, strong project management skills, analytical and problem-solving skills, and interest in AI, data quality, voice/audio technology, or machine learning infrastructure.

Job Description

Location: New York, NY or San Francisco, CA
Work model: Onsite, 5 days per week
Industry: AI Data / Voice AI / Machine Learning Infrastructure
Compensation: Competitive base salary up to $200,000 + equity, depending on experience

About the Company

Our partner is a fast-growing AI data company building high-quality audio and voice datasets for leading AI research labs and technology companies. The team operates with a research- and product-led approach, creating reusable datasets that can be owned, improved, and iterated on over time, rather than only delivering one-off custom data projects. Their work helps AI teams train stronger models by improving the quality, structure, and usability of voice and audio data.

The Opportunity

Our partner is hiring a Data & Product Operations Lead to own the execution of complex data projects from start to finish. This person will sit at the center of operations, product, research, engineering, QA, and deployment teams, ensuring that datasets are delivered on time, meet a high quality bar, and are useful for machine learning model training.

This is a highly cross-functional role for a strong generalist who enjoys ambiguity, ownership, and fast-paced execution. The team is looking for operators who can manage projects, solve operational problems, work with technical teams, and help shape how high-quality data products are built at scale.

Responsibilities

  • Own end-to-end execution of voice and audio data projects, from project kickoff through delivery
  • Work cross-functionally with product, research, engineering, QA, and deployment teams
  • Manage workflows across internal teams, speakers, reviewers, and quality assurance processes
  • Ensure data projects meet required quality standards and delivery milestones
  • Identify process gaps, operational bottlenecks, and opportunities for automation
  • Partner with engineering and platform teams to troubleshoot bugs, improve tooling, and streamline workflows
  • Help define project requirements and translate business or research goals into operational plans
  • Maintain a high bar for data quality, usability, and consistency
  • Support multiple projects or workstreams as company priorities evolve

Requirements

  • 2+ years of experience in consulting, strategy & operations, business operations, investment banking, private equity, marketplace operations, startup operations, or another high-intensity operating environment
  • Strong project management skills with the ability to drive complex workstreams across multiple stakeholders
  • Comfort working in ambiguous, fast-changing environments
  • Strong analytical and problem-solving skills
  • Ability to work closely with technical, product, and research teams
  • Excellent communication skills and strong attention to detail
  • High ownership mentality and willingness to operate across both strategic and execution-focused work
  • Interest in AI, data quality, voice/audio technology, or machine learning infrastructure
  • Prior experience in a startup, marketplace, consulting, finance, or operationally complex business is a plus
Key Skills
? Key Skills in dark blue have been inferred based on similar industry roles
Data Quality Assurance Workflow Automation SQL Python JIRA Data Pipeline Tooling Machine Learning Strategy Project Management Quality Assurance

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