GamaLearn

Data Scientist

• Develop and implement data science models to enhance learning, assessment, and training platforms.
• Conduct data analysis, statistical analysis, and predictive modeling to identify trends and patterns in educational data.
• Develop machine learning models including logistic regression, random forest, and clustering algorithms tailored for educational purposes.
• Use psychometric methods like Item Response Theory and Rasch Models to improve assessment data quality.
• Create data visualizations and dashboards using Power BI and Tableau for educational stakeholders.
• Work with cross-functional teams, including educators and researchers, to understand requirements and deliver insights.
• Optimize ETL processes for data integration and preprocessing specific to educational datasets.
• Support the development of adaptive learning systems and personalized learning experiences through data-driven approaches.
• Implement and utilize Graph API and OData endpoints to integrate and analyze data from various sources.
• Work with large language models (LLMs) and retrieval-augmented generation (RAG) techniques to enhance educational tools and provide personalized learning experiences.
• Leverage vector databases to store and retrieve high-dimensional data efficiently.

Data Science