Data Science ML Engineer

Must Have Technical/Functional Skills; 7-10 hands-on experience Python with expertise in pandas, NumPy, scikit-learn, matplotlib and seaborn. Strong understanding of ML evaluation metrics across classification and regression use cases. Experience with Databricks Notebooks and PySpark for handling large model outputs in parquet format. Experience in working with PDF generation libraries. Knowledge of MLFLow, model registries or production ML monitoring platforms.