Head of Research (DataLab) at Protege

Protege is building a platform to solve AI’s biggest unmet need: secure, efficient, and privacy-centric exchange of AI training data. The company is backed by top-tier investors and partners with leading AI teams, aiming to become one of the largest players in AI and tech.

The DataLab is Protege’s research arm, tackling foundational challenges in data for AI. The team bridges research theory and data deployment, focusing on questions like:

• What should agentic AI be trained to do?
• How to quality-control large-scale corpora?
• How to build evaluation datasets that reflect real-world needs?

DataLab is a fast-moving, high-trust team prioritizing scientific rigor and impact.

The Role

The Head of Research will lead Protege’s DataLab as a strategic research function, defining the research agenda, building experimentation systems, and ensuring research directly informs product direction, customer strategy, and platform capabilities.

This is a leadership and builder role, requiring:

• Setting a clear research roadmap.
• Managing and scaling a high-performing team.
• Partnering across Product, Engineering, GTM, and Leadership.
• Translating technical questions into practical frameworks, measurable experiments, and actionable recommendations.

You will also work closely with GTM to bring technical credibility to sales, delivery, and partner conversations.

What You'll Do

• Define and lead the research strategy for Protege’s DataLab, aligning experimentation with company priorities and product direction.

• Partner closely with Product, Engineering, and GTM teams to identify high-value research opportunities tied to AI data quality, evaluation, and marketplace performance.

• Design and oversee experiments evaluating dataset quality, model performance, synthetic data workflows, and privacy-preserving methodologies.

• Build scalable systems for benchmarking, labeling quality analysis, and training data evaluation across multiple AI modalities.

• Serve as a customer-facing research partner to GTM, representing DataLab in sales, technical discovery, delivery, and customer strategy conversations.

• Translate ambiguous technical questions into clear research frameworks, measurable hypotheses, and actionable recommendations.

• Publish internal research findings that directly influence product decisions, customer strategy, and platform capabilities.

• Lead, manage, and scale a high-performing team of researchers and data scientists, driving execution, technical excellence, and career development.

• Establish operational rigor around experimentation, reproducibility, and research documentation.

• Represent Protege externally through technical conversations with customers, partners, and the broader AI ecosystem.

• Stay at the forefront of advancements in foundation models, evaluation methodologies, data infrastructure, and AI alignment research.

What Success Looks Like

30 Days: Learn and Assess

• Build a deep understanding of Protege’s platform, customer workflows, and current research priorities.
• Meet cross-functional stakeholders across Product, Engineering, GTM, and Leadership.
• Audit current Data Lab workflows, experimentation infrastructure, and evaluation methodologies.
• Identify immediate opportunities to improve research velocity, rigor, and cross-functional communication.

60 Days: Establish Direction and Build Momentum

• Deliver a clear research roadmap aligned to company priorities and platform differentiation.
• Launch initial experiments focused on data quality, evaluation systems, or marketplace optimization.
• Introduce standardized processes for experiment tracking, documentation, and reproducibility.
• Develop hiring plans and organizational structure for scaling the Data Lab function.

90 Days: Drive Measurable Impact

• Deliver research insights influencing product roadmap decisions or customer outcomes.
• Demonstrate measurable improvements in experimentation speed, evaluation quality, or data performance metrics.
• Establish Protege’s Data Lab as a trusted strategic partner across Engineering, Product, and GTM.
• Recruit, onboard, and effectively lead key technical talent to support long-term research initiatives.

What We're Looking For

• Led impactful research initiatives in AI, machine learning, data infrastructure, or applied research environments.
• Built and managed high-performing research teams with autonomy, technical rigor, and fast execution cycles.
• Experience partnering directly with customers, GTM teams, or external stakeholders in applied technical settings.
• Developed frameworks for evaluating model performance, dataset quality, synthetic data, or large-scale experimentation systems.
• Experience operating in ambiguous, fast-moving environments with evolving priorities.
• Strong ability to communicate complex technical findings to both technical and non-technical audiences.
• Ownership of cross-functional initiatives spanning research, engineering, product, and go-to-market teams.
• Track record of translating research into practical systems, tools, or customer-facing impact.
• Experience working with modern AI systems, foundation models, LLM evaluation workflows, or privacy-centric data methodologies.
• High judgment, strong prioritization skills, and comfort making decisions with incomplete information.
• Motivated by building from first principles and solving foundational problems in AI infrastructure.