Data Scientist - Analytics & Reporting

Overview:

Clarium is seeking a highly skilled and analytical Performance Engineer with strong expertise in predictive modeling, data analysis, and reporting. The ideal candidate will play a critical role in analyzing performance data and supporting the scalability and efficiency of our OpenShift container platform (OCP) and legacy application environments. If you’re passionate about data-driven insights and performance engineering, we invite you to apply for this exciting opportunity.

Key Responsibilities:

• Maintain and enhance predictive models for performance engineering and capacity forecasting across OpenShift and legacy systems.
• Analyze production usage data to identify trends, anomalies, and capacity constraints.
• Collect and consolidate performance data from various sources (monitoring tools, logs, telemetry systems, etc.).
• Compare real-world usage with test environment simulations to refine forecasting models.
• Develop and maintain dashboards and visual reports on capacity headroom and performance metrics.
• Monitor infrastructure performance (CPU, memory, disk, etc.) and proactively identify optimization opportunities.
• Collaborate with engineering, DevOps, and business stakeholders to align capacity plans with future demand.
• Provide data-driven insights and recommendations to ensure optimal system performance and scalability.
• Document capacity planning strategies, models, and best practices.

Must-Have Skills:

• 7+ years of experience in data analysis, predictive modeling, or performance engineering.
• Strong hands-on experience with OpenShift container platform infrastructure.
• Solid background in data analysis and performance reporting.
• Excellent analytical thinking and problem-solving skills.
• Strong communication and collaboration skills.
• High attention to detail and accuracy.

Preferred Qualifications:

• Experience with containerization platforms (e.g., Docker, Kubernetes).
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud).
• Experience with monitoring/logging tools (e.g., Prometheus, Grafana, ELK).
• Proficiency in data visualization tools (e.g., Tableau, Power BI).
• Working knowledge of scripting languages (e.g., Python, Bash).
• Exposure to performance testing tools (e.g., JMeter, LoadRunner, Gatling).
• Understanding of DevOps methodologies and ITIL practices.
• Experience with agile project management tools and methodologies.
• Familiarity with business intelligence or data warehousing concepts.