Partnerships Operations Lead (Healthcare)
ProtegeAbout the role
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.
Role Overview:
We’re looking for a Partnerships Operations Lead (Healthcare) to operationalize and scale the data partner ecosystem that powers Protege’s healthcare AI products.
You will own execution — ensuring each healthcare partner is successfully onboarded, technically integrated, commercially aligned, and consistently delivering on customer engagements.
You will sit at the intersection of partnerships, science, product, and customer delivery — translating signed agreements into reliable, high-quality data supply.
This role requires deep understanding of healthcare data operations, strong cross-functional coordination, and the ability to manage complexity across multiple concurrent deals.
Key Responsibilities:
Operationalize Healthcare Data Partnerships
Lead onboarding of new healthcare data partners, establishing repeatable operational playbooks
Coordinate secure data access, querying workflows, and transfer mechanisms
Partner with Product and Engineering to align on ingestion, normalization, and technical setup
Ensure privacy, compliance, and governance requirements are properly implemented in collaboration with Legal and Compliance
Develop structured processes to scale partner onboarding efficiently
Evaluate Data Readiness & Quality
Conduct structured evaluations of partner datasets across EHR, imaging, claims, genomics, device, or real-world data
Partner with DataLab to assess data completeness, quality, modality coverage, and fitness for AI training use cases
Collaborate with scientific teams to support feasibility assessments for customer projects
Identify data gaps, operational risks, and areas requiring remediation
Establish partner performance scorecards tracking responsiveness, reliability, and data quality
Execute on Customer-Specific Data Engagements
Align partners on project requirements, qualification criteria, and delivery timelines
Track feasibility analyses and ensure timely, accurate partner responses
Monitor deal progress from qualification through fulfillment
Coordinate data delivery milestones and resolve execution bottlenecks
Proactively surface risks to internal stakeholders and propose mitigation plans
Drive Ongoing Partner Performance & Value
Ensure partners are fulfilling their obligations across individual customer engagements
Monitor utilization, revenue contribution, and operational performance
Partner with the Strategic Partnerships Lead to identify expansion opportunities
Maintain aligned communication between partners and internal teams
Continuously improve operational workflows to increase reliability and speed
Represent Operational Excellence in the Market
Serve as the primary execution point of contact for healthcare data partners
Build trusted relationships grounded in transparency, responsiveness, and accountability
Reinforce Protege’s position as the premier platform for responsible AI data collaboration
About You:
6–10+ years of experience in healthcare data operations, partnerships execution, data program management, or similar roles
Deep understanding of healthcare data modalities (EHR, imaging, claims, genomics, device, or real-world data) and how they are operationalized
Experience onboarding healthcare data partners or integrating health system or aggregator datasets into platforms
Technical ability to work with data in Snowflake, Databricks, and other tools.
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