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Protege is building a platform to securely and efficiently enable AI training data partnerships in life sciences. This role focuses on business development and partnerships, shaping data licensing strategies, and coordinating with internal teams to accelerate collaboration with genomics, transcriptomics, and multi-omics data providers.
You will work with labs, biobanks, and diagnostics companies to secure access, clarify provenance and consent, and drive agreements that unlock data assets for
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.