Define evaluation frameworks for AI-powered education tools (e.g., LLM-based systems, adaptive learning systems)
Design and analyze experiments across structured and unstructured data (A/B testing, quasi-experimental methods, causal inference)
Translate findings into clear recommendations for product and research partners
Collaborate cross-functionally with Product, Engineering, Learning Science, and external partners
Contribute to best practices for responsible AI evaluation, including bias, fairness, and reliability

Requirements

5+ years of experience in data science, applied research, or quantitative analysis
Proficiency in the modern data science tech stack, including Python, SQL, ML
Familiarity with evaluation of generative AI systems (e.g., rubric-based evaluation, human-in-the-loop evaluation)
Ability to communicate complex findings to technical and non-technical audiences
Experience collaborating with cross-functional teams (product managers, engineers, researchers) in a fast-paced development environment

Benefits

Provides a generous employer match on employee 401(k) contributions to support planning for the future.
Paid time off to volunteer at an organization of your choice.
Funding for select family-forming benefits.
Relocation support for employees who need assistance moving

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data scienceapplied researchquantitative analysisPythonSQLmachine learningA/B testingcausal inferenceevaluation of generative AI systemsrubric-based evaluation

Soft Skills

communicationcollaborationcross-functional teamworkability to translate findingsresponsible AI evaluation