🛠 Tech Stack

💼 About This Role

You'll develop machine learning models to predict student dropout risk and detect fraud in school financial systems. You will manage end-to-end data science workflows in a public sector environment, translating complex data into actionable insights for education and financial governance.

🎯 What You'll Do

• Develop ML models to predict student dropout risk.
• Design fraud detection models for school financial systems.
• Manage end-to-end data science workflows from extraction to deployment.
• Translate analytical findings into dashboards for stakeholders.

📋 Requirements

• Bachelor's degree in Data Science or related field.
• Proven experience in fraud detection or anomaly detection projects.
• Advanced proficiency in Python and Pandas, Scikit-learn, XGBoost.
• Experience with Microsoft Fabric and Azure Machine Learning.

✨ Nice to Have

• Experience in public sector projects.
• Experience in fintech or auditing environments.
• MLOps practices.

🎁 Benefits & Perks

• 💼 Competitive compensation aligned with experience.
• 🌍 High-impact projects in education and public policy.
• ☁️ Advanced cloud-based AI technologies exposure.
• 📈 Professional growth opportunities in data science and AI.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Final Interview· 45 min