Head of Research, DataLab

About the role

The Head of Research will lead Protege's DataLab as a strategic research function focused on answering the hardest questions about data for AI. This person will define the research agenda, build rigorous systems for experimentation and evaluation, and ensure DataLab's work directly informs product direction, customer strategy, and platform capabilities.

Responsibilities

• Define and lead the research strategy for Protege's Data Lab, 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 that evaluate 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 while translating research depth into practical guidance that helps Protege deliver value to our partners and customers.
• 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 across the Data Lab organization.
• 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.

Requirements

• Led impactful research initiatives in AI, machine learning, data infrastructure, or applied research environments where outcomes influenced product or business strategy.
• Built and managed high-performing research teams that operated with autonomy, technical rigor, and fast execution cycles.
• Experience partnering directly with customers, GTM teams, or external stakeholders in applied technical settings, with the judgment to represent both the research and business value of complex AI/data work clearly and credibly.
• Developed frameworks for evaluating model performance, dataset quality, synthetic data, or large-scale experimentation systems.
• Experience operating in ambiguous, fast-moving environments where priorities evolved quickly and execution mattered.
• Strong ability to communicate complex technical findings to both technical and non-technical audiences.
• Demonstrated 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.

Qualifications

• PhD in Computer Science, Applied Mathematics, Statistics, or a related field.
• 5+ years of experience in AI, machine learning, data science, or related fields.
• Proven track record of leading and managing research teams.
• Experience in defining and executing research strategies that drive innovation and impact.
• Strong background in data quality, model performance evaluation, and experimental design.
• Excellent communication and presentation skills, able to articulate technical concepts to non-technical stakeholders.
• Ability to work independently and collaboratively with cross-functional teams.
• Passionate about advancing the state-of-the-art in AI data infrastructure and research methodologies.

Skills

• Expertise in AI, machine learning, data science, and related fields.
• Strong analytical and problem-solving skills.
• Experience with data collection, preprocessing, and analysis techniques.
• Knowledge of foundational AI models and their applications.
• Experience with research methodologies and statistical analysis.
• Ability to communicate complex technical ideas to both technical and non-technical audiences.
• Experience with project management and prioritization.

Benefits

• Competitive compensation package including base salary, equity, and benefits.
• Flexible work arrangements to support work-life balance.
• Continuous learning and professional development opportunities.
• Collaborative and inclusive workplace culture.
• Opportunities to contribute to groundbreaking research and technology.

Pay

Competitive compensation package including base salary, equity, and benefits.

Schedule

Full-time position with flexible work arrangements to support work-life balance.