Overview
Adaptativamente is an edtech platform that helps students learn mathematics through dynamic and personalized exercises. As a Data Scientist, my core work was building the recommendation engine behind the platform — a model that decides in real time which exercise is best for each student based on their learning history, using a combination of neural networks and causal inference methods.
Key Achievements
- Created a machine learning model using neural networks and causal inference to estimate the optimal math exercise to recommend to each student, maximizing their learning outcomes.
- Presented the model's development and explained its features and methodology to upper management.
- Researched multiple state-of-the-art statistical methods in Python and R to enhance the model's performance metrics.
- Collaborated with the team to collect and structure over 10,000 student score records and integrate them into the model automatically.