Job Details
Job Description
Key Responsibilities:
Monitor the health and performance of production data science systems, including predictive models, dashboards, and data pipelines.
Diagnose issues such as data drift, performance degradation, or infrastructure instability, and implement timely fixes.
Automate monitoring tasks and health checks related to data quality, forecast accuracy, and pipeline execution.
Update and patch environments and applications, ensuring smooth operation across versions and dependencies.
Collaborate with engineers and data scientists to refactor and optimize code for long-term maintainability.
Maintain detailed documentation and change logs to ensure knowledge sharing and traceability.
Support incident response, including root cause analysis and post-incident improvements.
Ensure compliance with all applicable data privacy, security, and regulatory standards.
Requirements:
Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
Minimum 2 years’ experience in a data engineering, MLOps, or system maintenance role.
Solid understanding of data science production workflows, including pipelines and model lifecycle.
Proficient in Python and R with strong debugging and refactoring capabilities.
Confident in SQL and managing large-scale datasets in production.
Experience with CI/CD, Git, and containerization tools like Docker.
Familiarity with cloud infrastructure (AWS, GCP, or Azure) and DevOps best practices.
Strong analytical, problem-solving, and communication skills.
Contact Hire Resolve for your next career-changing move.
Our client is offering a highly competitive salary for this role based on experience.
Apply for this role today, contact Gaby Turner at [email protected] or on LinkedIn
You can also visit the Hire Resolve website: hireresolve.us or email us your CV: [email protected]