Data Scientist in QE

il y a 2 semaines

AnyMartinRieux, Hauts-de-France Qualitest acq Temps plein

Are you interested in working with the World's leading AI-powered Quality Engineering Company? Ready to advance your career, team up with global thought leaders across industries and make a difference every day? Join us at Qualitest

We are looking for a Data Scientist in QE to join our growing team in Argentina/México

Role - Data Scientist in QE

Location - Remote from 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. You'll design automated testing frameworks, validate machine learning models, and collaborate with cross-functional teams to uphold the highest standards of data quality and model integrity.

Key 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

Required 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).

Preferred Skills
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.

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