Get a reply from this employer
Your resume and cover letter, tailored to exactly what they’re hiring for.
Protege is building a platform to unlock AI training data by enabling secure, privacy-centric data exchanges. We are seeking a Partnerships Lead to drive external relationships with genomics and life sciences organizations, structuring data licensing and collaboration opportunities.
You will coordinate NDAs, determine provenance and permitted uses, and align pricing and statements of work with Commercial and Healthcare Operations.
Company Overview:
We are building Protege to solve the biggest unmet need in AI — getting access to the right training data. The process today is time intensive, incredibly expensive, and often ends in failure. The Protege platform facilitates the secure, efficient, and privacy-centric exchange of AI training data.
Solving AI’s data problem is a generational opportunity. We’re backed by world-class investors and already powering partnerships with some of the most ambitious teams in AI. The company that succeeds will be one of the largest in AI — and in tech.
We’re a lean, fast-moving, high-trust team of builders who are obsessed with velocity and impact. Our culture is built for people who thrive on ambiguity, own outcomes, and want to shape the future of data and AI.
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 the appropriate internal reviewers.
Work with Commercial on pricing, licensing structures, and statements of work, and coordinate activation with Healthcare Operations and Solutions.
Build trusted partner relationships, surface underused molecular data assets, and recommend partnerships that address customer needs and gaps in the omics portfolio.
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; able 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.