Description:
10 years hands-on with Python for machine learning especially XGBoost, scikit-learn and NumPy/pandas. Proficiency in PySpark for reading, transforming and analyzing large datasets stored in parquet.Experience in validating or reverse engineering ML models from business logic or legacy implementation.Exposure to Java-based ML libraries or understanding of how internals map across languages.Hands-on with Python frameworks for meta-modelling libraries. Roles & Responsibilities: Interpret data tran
Jan 29, 2026;
from:
dice.com