Company: Global Technology organization

Key Skills: Containerization (Docker, Kubernetes), DevOps, Python, AWS, Kubernetes, GitHub

Roles and Responsibilities:

Provide L3 support/ development for complex platform incidents escalated
Troubleshoot issues related to workspace provisioning, model execution, job orchestration, and data connectivity.
Perform root cause analysis (RCA) and implement permanent fixes for recurring issues.
Manage platform operations, including upgrades, patching, monitoring, and performance tuning & workspaces. Ensure uptime as a part of the KPI and SLA
Support data science environments (Python, R, Git) used by analytics and AI/ML teams.
Enable ML lifecycle activities including experimentation, training, and deployment.
Implement automation and monitoring improvements to enhance platform reliability.

Skills Required:

Experience Requirements

7-10 years of overall IT experience
4+ years supporting data science or analytics platforms
Experience in life sciences or pharmaceutical environments
Familiarity with regulated environments (GxP), ITSM tools, and change/release management.

Nice to Have

Kubernetes administration/ Domino data lab certification
Cloud certifications (AWS/Azure)
Exposure to clinical analytics, research data platforms, or AI/ML model development.

Education: Bachelor's Degree in related field

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