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