Data Scientist

• Develop and deploy advanced machine learning models: Design, implement, and evaluate machine learning models for tasks such as personalized learning recommendations, student performance prediction, content optimization, and educational resource analysis.
• Conduct in-depth data analysis: Explore and analyze large datasets from various sources (e.g., student learning platforms, assessment data, user behavior logs) to identify trends, patterns, and insights that inform product development and educational strategies.
• Design and execute experiments: Develop and implement A/B testing and other experimental designs to evaluate the effectiveness of educational interventions and product features.
• Communicate insights and recommendations: Effectively communicate complex data insights and recommendations to both technical and non-technical audiences through visualizations, presentations, and reports.
• Collaborate with cross-functional teams: Work closely with product managers, engineers, educators, and researchers to define project goals, develop data-driven solutions, and ensure successful implementation.
• Stay up-to-date with the latest advancements: Continuously research and evaluate new machine learning techniques, tools, and best practices relevant to the education technology domain.
• Contribute to the development of data infrastructure: Work with data engineers to ensure data quality, accessibility, and scalability.
• Work on building products and features that use Generative AI

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