Über
Must Have Technical/Functional Skills: • 7-10 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 transformation logic and validate feature pipelines from existing Java implementations. • Run Python-converted models on historical datasets and validate output metrics against Java model benchmarks. • Collaborate with model validation teams to review performance, consistency and explain metric deviations if any. • Design unit tests and validation scenarios to support each migrated models readiness for signoff. • Ingest model input data from parquet files using PySpark and pandas to reproduce training and scoring workflows. • Conduct EDA and spot-check row-level predictions where needed Collaborate with the customer team to • understand the logic, structure and parameters of the Java-based XGBoost models.
Salary :130,000-145,000/Per Annum
Sprachkenntnisse
- English
Hinweis für Nutzer
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