Digital Twin / Asset Performance Engineer

Position Overview

The Digital Twin / Asset Performance Engineer develops and maintains digital twin models of offshore assets, integrating real-time operational data with engineering models to enable predictive maintenance, performance optimization, and life extension decision-making. This role sits at the intersection of data science, engineering, and asset management, representing a rapidly growing discipline in the offshore sector.

Key Responsibilities

• Develop and maintain digital twin models for offshore assets (platforms, FPSOs, subsea systems, wind turbines) integrating 3D models, simulation, and real-time data
• Design and implement asset performance monitoring systems using sensor data, SCADA, and condition monitoring inputs
• Develop predictive analytics models for equipment failure prediction, remaining useful life estimation, and maintenance optimization
• Create data integration architectures connecting OT (SCADA, DCS) and IT (ERP, CMMS) systems with digital twin platforms
• Perform structural and process simulations using digital twin models to support integrity assessment and life extension decisions
• Develop dashboards and visualization tools for asset performance reporting and decision support
• Collaborate with operations, maintenance, and engineering teams to identify digital twin use cases and prioritize deployment
• Manage data quality, governance, and security for digital twin and asset performance data ecosystems
• Evaluate and select digital twin technology platforms and analytics tools for offshore asset applications
• Support change management and training to drive adoption of digital twin solutions across operational teams

Qualifications

Required

• Education: Bachelor's degree in Engineering (Mechanical, Process, Subsea) or Computer Science/Data Science; Master's degree preferred
• Certifications: Data science or ML certification preferred; asset management certification (IAM) advantageous; cloud platform certifications (Azure, AWS) beneficial
• Experience: Minimum 5 years in asset integrity, engineering, or data science with at least 2 years in digital twin or predictive analytics applications
• Technical Skills: Digital twin platforms (Siemens MindSphere, AVEVA, Bentley iTwin); data analytics (Python, R); ML/AI model development; OT/IT integration; 3D modeling; asset management systems

Preferred

• Experience deploying digital twins for offshore oil & gas or wind assets
• Cloud architecture and edge computing experience
• Structural or process simulation background (FEA, CFD, process simulation)
• Change management and digital transformation delivery experience