Design and implement scalable data architectures that support multiple software platform initiatives.

Integrate data across software telemetry, hardware platforms, AI workloads, validation systems, engineering tools, benchmarking environments, and business systems.

Develop and maintain reliable data pipelines, data models, transformation processes, and reporting frameworks.

Define data governance, quality, lineage, security, and lifecycle management standards.

Build machine learning models that identify performance trends, anomalies, optimization opportunities, and operational risks.

Apply advanced statistical methods to understand workload behavior, system utilization, software effectiveness, and customer usage patterns.

Develop workload characterization models and comparative analyses across different platform configurations and operating conditions.

Build predictive models for performance, reliability, capacity planning, and system behavior.

Design and execute experiments that validate hypotheses and measure the effect of software or platform changes.

Develop executive dashboards, scorecards, and visualizations that provide meaningful visibility into platform health and key business metrics.

Partner with engineering teams to translate data-driven insights into product and platform improvements.

Present analytical findings and recommendations to technical teams, business leaders, and executive stakeholders.

Senior Data Scientist – Edge AI Platforms & Systems Analytics

Responsibilities

Qualification

Preferred

Benefits

Company

Hp

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