Artist Curation Operations Lead

Artist Curation Operations Lead Location:

Hybrid onsite in

Cupertino, CA Schedule :

40 hours

Duration:

12 months

Pay:

$95

• 97.

86 DOE The Planet Group is looking for an Artist Curation Operations Lead to join our well-known Fortune 500 client on a 12-months contract, working a hybrid onsite schedule in Cupertino, CA Artist Curation Operations Lead |

Qualifications:

5+ years in operations, program management, or technical product roles with meaningful exposure to AI/ML-driven workflows. Demonstrated experience translating operational or product problems into ML requirements and working directly with data scientists and engineers through model development cycles. Experience evaluating model outputs

• designing eval sets, quality metrics, error analysis, and human feedback loops.

Experience designing or specifying review/annotation tooling that surfaces AI inputs to human reviewers. Conceptual understanding of core analytics principles (sampling, hypothesis testing, statistical measurement). Proven ability to produce executive-ready written narratives and presentations. Track record of leading ambiguous initiatives end-to-end with minimal direction.

Preferred Qualifications:

Experience in the music industry or with music metadata, catalogs, rights data, or artist-facing products. Familiarity with entity resolution / disambiguation problems (artists, works, identities). Exposure to LLM-based workflows, prompt evaluation, or agentic automation. Experience collaborating with international stakeholders or managing cross-cultural projects is a plus. Comfort querying data (SQL or similar) to investigate issues independently. Experience managing vendor or outsourced review teams. Tableau or comparable BI tooling. A genuine passion for music and curiosity about the systems that power the modern music industry. Artist Curation Operations Lead |

Description:

Lead artist curation operations end-to-end

• covering artist pages, bios, images, disambiguation, and the expanding surface area of artist-facing data
• and serve as the primary operational owner and escalation point for vendor teams raising curation questions. Bridge communication between business stakeholders and technical teams (Data Science, Engineering, AI/ML), ensuring operational needs are clearly understood and technical tradeoffs are clearly communicated back. Translate operational challenges into technical requirements
• from artist disambiguation to image quality to bio accuracy
• into clear, actionable specifications that engineering and data science teams can execute against. Break down ambiguous problems like artist disambiguation into well-scoped, prioritized workstreams, sequenced by impact. Start with the highest-leverage slice; iterate from there. Evaluate technical proposals and model outputs
• participate in design reviews and design eval frameworks (golden sets, quality metrics, error analysis, human-in-the-loop feedback) to judge whether AI/ML solutions are ready for production.

Design and iterate on manual review tooling that surfaces AI-generated inputs (confidence scores, candidate matches, suggested actions) to accelerate reviewer throughput and accuracy. Identify opportunities to apply ML models, agentic workflows, and automation to pressing artist curation problems

• running lightweight ROI and impact analyses to distinguish short-term tactical wins from long-term structural solutions. Communicate upward
• build clear, compelling decks and present progress, tradeoffs, and recommendations to leadership.

Partner cross-functionally with Engineering, Data Science, Product, Analytics, and peer Operations teams (including Partner Operations and Data Strategy) to surface interdependencies and align priorities.