Intern, Data Science

📋 Description

• Develop a refined credit risk model with improved predictive power.
• Incorporate alternative data sources to improve interpretability.
• Evaluate new feature sets from transactional and bank data.
• Test ML techniques to optimize risk assessment.
• Data cleaning and feature engineering for modeling.
• Create data visualizations to communicate results.

🎯 Requirements

• Proficient in Python (Pandas, NumPy) or R for data analysis.
• Experience with ML libraries like scikit-learn and TensorFlow.
• Familiar with regression, classification, clustering algorithms.
• Create visualizations with Matplotlib, Seaborn, Tableau.
• Strong stats methods for model evaluation and hypothesis testing.
• Critical thinking and data-driven problem solving.
• Clear written and verbal communication to non-technical stakeholders.

🎁 Benefits

• 10-12 week internship with real-world data science projects.
• Mentorship from experienced data scientists.
• Exposure to credit risk modeling and business impact.