Data Science Trainee (AlmaBetter) — hands-on ML training with dataset preparation, EDA, feature engineering, and model evaluation.
Don't disclose
Served as a Data Science Trainee where the work focused on preparing datasets and building ML features/models rather than manual annotation. Applied data cleaning and feature engineering to transform raw data into model-ready inputs for supervised and unsupervised learning tasks. Conducted exploratory analysis and evaluated modeling outcomes to support downstream AI use cases. • Performed EDA and derived insights from datasets using visualization tools. • Built clustering and classification pipelines including feature engineering steps. • Handled imbalanced data using SMOTE/Tomek (as applicable in projects). • Tuned hyperparameters and assessed performance using metrics like silhouette score and recall.
2022 - Present