Description

You will own the testing and validation of data pipelines and machine learning models. Your work ensures statistical integrity, data quality, and model reliability in production.

Responsibilities

• Develop and maintain automated testing frameworks for data pipelines and ML models.
• Design and execute test cases to validate statistical models, algorithms, and data transformations.
• Monitor data quality, detect anomalies, and ensure consistency across datasets.
• Leverage real-world data and build synthetic datasets to simulate edge cases, stress-test models, and verify data security.
• Coordinate with end users to run human-in-the-loop and A/B tests, documenting results and performance metrics.

Required Skills

• 5+ years of experience in data science and AI/ML testing.
• Proficiency in Python and SQL for data manipulation and testing.
• Experience with testing frameworks such as PyTest or unittest.
• Hands-on experience with machine learning libraries including scikit-learn, TensorFlow, and XGBoost.
• Strong understanding of statistical testing, model validation, and data integrity principles.
• Familiarity with CI/CD pipelines and version control (e.g., Git, Jenkins).

Preferred Skills

• Experience with Oracle AI Data Platform or Oracle Cloud Infrastructure (OCI), including Medallion architecture.
• Familiarity with Azure Dev Ops (ADO) for test management and model monitoring tools.

Key Skills

Education

Any Graduate