Role Overview
As the Data Scientist, you will use statistical modelling, machine learning, and rigorous experimentation to generate insights from learner data and translate them into measurable product outcomes. You bridge raw data and decision-making, ensuring every product intervention is evidence- driven.
Key Responsibilities
• Build predictive models for learner outcomes: dropout risk, knowledge gaps, learning pace, and content recommendation.
• Design and analyse A/B experiments with rigorous statistical methodology and business metric alignment.
• Analyse large-scale learner interaction datasets to surface actionable patterns for product and curriculum teams.
• Develop and ship ML solutions end-to-end: from exploration to serialised models, API wrappers, and monitoring.
• Build dashboards and data narratives that communicate findings clearly to non-technical stakeholders.
• Partner with engineering on feature store design and pipeline automation for recurring model inputs.
• Run causal inference analyses to attribute learner outcomes to specific interventions or content changes.
• Document model assumptions, evaluation results, and limitations clearly for cross-functional review.
• Leverage cloud platforms and data pipelines to build, deploy, and monitor ML models in production environments.
• Build data visualisations and analytical reports that communicate findings clearly to non-technical product and government stakeholders.
Must-Have Skills
• Strong knowledge of Machine Learning, Statistics, and Data Analysis
• Proficiency in Python, SQL, and data science libraries
• Experience with data pre-processing, feature engineering, and model development
• Knowledge of predictive analytics, AI/ML models, and model evaluation
• Experience working with large datasets and data visualization tools
• Understanding of cloud platforms and data pipelines is preferred
• Strong analytical, problem-solving, and communication skills