Problem Translation & Modeling
- Convert social sector challenges into well-defined ML problems
- Design, implement, and optimize ML models and solutions
Data Management
- Collect, clean, preprocess, and transform data for modeling
- Perform exploratory data analysis and data mining
Model Training & Evaluation
- Train, validate, and evaluate ML/statistical models
- Define and track metrics to measure model performance and social impact
Deployment & Real-World Application
- Support deployment of scalable ML solutions in real-world settings
- Adapt models to constraints of large-scale, practical environments
Collaboration & Knowledge Sharing
- Work closely with engineers, domain experts, and social sector partners
- Document models, processes, and learnings
- Contribute to team knowledge sharing and continuous improvement
