Strategic Partnerships Manager, Omics and Genomics

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🔥 0 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

💰 Account Manager

👻 Ghost score 10%

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Grupo Protege

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1971

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

Artificial Intelligence • B2B • SaaS

Grupo Protege is an AI training data platform that connects AI developers with high-quality, ethically sourced training data. It serves both AI developers by providing a vast and rich collection of data for model training and data holders by enabling them to monetize their data while maintaining governance and control. The platform aims to streamline the data procurement process significantly, making it easier for developers to access the data they need efficiently.

📋 Description

• Qualify sequencing labs, biobanks, diagnostics providers, life sciences companies, and research consortia with genomics, transcriptomics, proteomics, or multi-omics data • Assess dataset differentiation through cohort composition, assay or sequencing methods, raw and processed data availability, quality documentation, and linked clinical or phenotype information • Coordinate NDAs, sample access, and DataLab evaluation • Clarify provenance, permitted uses, and consent or licensing restrictions with appropriate internal reviewers • Work with Commercial on pricing, licensing structures, and statements of work • Coordinate activation with Healthcare Operations and Solutions • Build trusted partner relationships • Surface underused molecular data assets • Recommend partnerships addressing customer needs and gaps in the omics portfolio

🎯 Requirements

• Experience in partnerships, business development, or data licensing in life sciences, with a track record of advancing external relationships into execution • Direct experience with genomics and working knowledge of transcriptomics, proteomics, and the broader multi-omics landscape • Familiarity with raw and processed sequencing files such as FASTQ, BAM, and VCF • Ability to discuss dataset quality, provenance, and relevant documentation with technical stakeholders • Understanding of how cohort characteristics, assay methods, and linked clinical or phenotype information affect dataset usefulness • Ability to surface consent, de-identification, and data-use restrictions for expert review • Strong cross-functional coordination and judgment in an early-stage environment • Experience with AI data partnerships, research data commercialization, or sample evaluation workflows

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