Olenick
Job Summary
We are looking for a Data Scientist in QE to join our growing team in Argentina/México. This hybrid role combines the rigor of software testing with the creativity of data science to ensure the accuracy, reliability, and performance of our data‑driven products. The position is remote and focuses on designing automated testing frameworks, validating machine learning models, and collaborating across teams to uphold the highest standards of data quality and model integrity. Responsibilities
Develop and maintain automated testing frameworks for data pipelines and machine learning models. Design and execute test cases to validate statistical models, algorithms, and data transformations. Monitor data quality, detect anomalies, and ensure consistency across datasets. Collaborate with data scientists, engineers, and QA teams to define test strategies and acceptance criteria. Perform exploratory data analysis to uncover hidden issues in data or model behavior. Leverage real‑world data and build synthetic datasets to simulate edge cases, stress‑test models, ensure unbiased predictions, and verify data security. Coordinate with end users to run human‑in‑the‑loop and A/B tests. Document test results, bugs, and performance metrics to support continuous improvement. Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field. 3+ years of experience in data science and AI/ML testing. Proficiency in Python, SQL, and testing frameworks (e.g., PyTest, unittest). Experience with machine learning libraries (e.g., scikit‑learn, TensorFlow, XGBoost). Strong understanding of statistical testing, model validation, and data integrity principles. Familiarity with CI/CD pipelines and version control (e.g., Git, Jenkins). Experience using Oracle AI Data Platform / Oracle Cloud Infrastructure (OCI) including Medallion architecture. Strong mastery of SQL. Knowledge of MLOps and model monitoring tools. Familiarity with Azure Dev Ops (ADO) for test management. Excellent communication and documentation skills. If you like what you have read, send us your resume and let’s start talking!
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We are looking for a Data Scientist in QE to join our growing team in Argentina/México. This hybrid role combines the rigor of software testing with the creativity of data science to ensure the accuracy, reliability, and performance of our data‑driven products. The position is remote and focuses on designing automated testing frameworks, validating machine learning models, and collaborating across teams to uphold the highest standards of data quality and model integrity. Responsibilities
Develop and maintain automated testing frameworks for data pipelines and machine learning models. Design and execute test cases to validate statistical models, algorithms, and data transformations. Monitor data quality, detect anomalies, and ensure consistency across datasets. Collaborate with data scientists, engineers, and QA teams to define test strategies and acceptance criteria. Perform exploratory data analysis to uncover hidden issues in data or model behavior. Leverage real‑world data and build synthetic datasets to simulate edge cases, stress‑test models, ensure unbiased predictions, and verify data security. Coordinate with end users to run human‑in‑the‑loop and A/B tests. Document test results, bugs, and performance metrics to support continuous improvement. Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field. 3+ years of experience in data science and AI/ML testing. Proficiency in Python, SQL, and testing frameworks (e.g., PyTest, unittest). Experience with machine learning libraries (e.g., scikit‑learn, TensorFlow, XGBoost). Strong understanding of statistical testing, model validation, and data integrity principles. Familiarity with CI/CD pipelines and version control (e.g., Git, Jenkins). Experience using Oracle AI Data Platform / Oracle Cloud Infrastructure (OCI) including Medallion architecture. Strong mastery of SQL. Knowledge of MLOps and model monitoring tools. Familiarity with Azure Dev Ops (ADO) for test management. Excellent communication and documentation skills. If you like what you have read, send us your resume and let’s start talking!
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