Data Scientist– Python & PySpark

Remote Job

• 7-10 years hands-on with Python for machine learning – especially XGBoost, scikit-learn and Num Py/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.

• 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 model’s 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: ,000 per annum