Data Scientist Student 2026 H2

Prepare and engineer features from structured and unstructured sources; write clear, reproducible data pipelines and SQL queries. Implement, train, and evaluate models (regression, classification, clustering, simple neural networks) with attention to cross-validation, hyperparameter tuning, and performance monitoring. Develop notebooks and modular Python code (with unit tests and documentation) and help package work for reproducibility (Git, virtual environments, Docker basics). Collaborate in code reviews, experiment tracking, and model validation; learn essentials of MLOps (model versioning, basic deployment concepts). Currently enrolled in or recently graduated from Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field. Solid grounding in statistics, basic probability, and core machine learning concepts (bias/variance, regularization, evaluation metrics). Proficient in Python and familiar with common libraries (pandas, numpy). Strong emphasis on writ...