Data Scientist in QE
Role summary
We are seeking a Data Scientist in Test for a long-term contract role. This remote position focuses on ensuring the accuracy, reliability, and performance of data-driven products by combining data science and software testing principles. Key responsibilities include developing automated testing frameworks for data pipelines and ML models, validating statistical models and algorithms, monitoring data quality, and collaborating with cross-functional teams. The role requires proficiency in Python, SQL, testing frameworks, ML libraries, and statistical testing, with a minimum of 3 years of experience in data science and AI/ML testing.
Data Scientist in QE
Location: Remote
Duration: Long term contract
We are looking for a Data Scientist in Test to join our growing team in United States
Top 3 Must Haves:
- 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.
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