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# Data Scientist, Education

- **Company:** Generative Ai
- **Location:** Redwood City, CA, United States
- **Experience:** Expert
- **Salary:** $190,000.0 - $261,800.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Integrated Development Environments, Python (Programming Language), Machine Learning, SQL Databases, Unstructured Data, Application Enhancement Tool, Large Language Models, Generative AI
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/senior-data-scientist-education-learning-commons-8134851

## About the Role

* 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

## Description

Learning Commons aims to scale proven learning science practices through AI-powered tools, datasets, and evaluation frameworks. As part of the Evaluators team, you will play a critical role in ensuring that AI and education products are grounded in rigorous, research-backed evaluation.

You will define and operationalize evaluation frameworks for AI-enabled learning tools, develop metrics and methodologies to assess quality and impact, and generate insights that inform product, research, and ecosystem decisions. This includes evaluating model performance, alignment to pedagogy, and real-world effectiveness in classrooms.

You will partner closely with Product, Engineering, Learning Science, and external researchers to ensure that evaluation is embedded throughout the product lifecycle-from early experimentation to scaled deployment. This role sits at the intersection of data science, learning science, and AI system evaluation.

What You'll Do

 * 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


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