Asset Performance Analytics (APA)

We are seeking an experienced GE SmartSignal / Asset Performance Analytics (APA) to drive predictive maintenance and AI-driven asset reliability initiatives across industrial operations. The role focuses on implementing, tuning, and scaling SmartSignal analytics solutions to detect early equipment failures, improve asset availability, and enable data-driven operational excellence.

The ideal candidate will have strong expertise in machine learning–based condition monitoring, industrial data analytics, and integration with enterprise asset management systems within the Oil & Gas / Manufacturing domain.

Roles & Responsibilities:

Implement, configure, and support GE SmartSignal (APA) models for critical assets (compressors, turbines, pumps, etc.).

Perform model training, tuning, validation, and lifecycle management using historical and real-time data.

Analyze anomalies, generate insights, and collaborate with operations teams for early fault detection and root cause analysis.

Integrate SmartSignal with systems like GE APM, PI System, SAP, Maximo and IoT platforms.

Manage data ingestion, cleansing, and feature engineering for high-quality analytics outcomes.

Develop dashboards, alerts, and reporting mechanisms for actionable insights.

Support APA program adoption, value realization, and continuous improvement initiatives.

Ensure compliance with cybersecurity, data governance, and enterprise architecture standards.

Qualifications & Requirements:

Experience: 7+ years

Domain: Oil & Gas, Petrochemicals, Power

Qualifications:

- Masters or BS degree in Mechanical/Chemical Engineering or equivalent

Application / Tools knowledge:

SmartSignal / APA Expertise: Model development, tuning, anomaly detection, alert configuration

Data & Analytics: Time-series data analysis, ML concepts, Python/R (preferred), data preprocessing

Industrial Systems: GE APM, OSIsoft PI, SCADA, DCS systems

Integration: APIs, middleware, integration with SAP PM, Maximo

Data Platforms: SQL, historian data, ETL pipelines

Cloud & Tools: Azure/AWS basics, visualization tools (Power BI/Tableau)