Availability & Reliability Engineer

About the role

The Availability & Reliability Engineer is a specialized role within the Wind Engineering division. You will serve as the primary architect of fleet performance data modeling, using advanced statistical and predictive analytics to drive the global energy transition. Your mission is to transform raw fleet data into actionable reliability models and high-fidelity availability forecasts that inform design decisions, service contracts, and customer expectations.

Responsibilities

• Availability Analytics
  • Downtime Diagnostics: Ingest and analyze massive datasets from the global wind fleet to identify the primary drivers of turbine unavailability.
  • Root Cause Quantification: Quantify the impact of specific failure modes on overall fleet uptime, distinguishing between technical failures (Reliability) and service delays (Maintainability).
  • Predictive Inventory Forecasting: Create data-driven projections for spare part demand to enable immediate return-to-service for down turbines without maintaining excessive or redundant inventory levels.
• Reliability Modeling
  • Probabilistic Modeling: Develop and maintain component-level reliability models to predict the life cycle of critical turbine systems.
  • Design Verification: Collaborate with design engineers to set reliability targets for new products and verify that replacement parts meet or exceed the reliability of failed components.
  • Predictive Diagnostics: Assist in building advanced analytics aimed at early detection of degradation, shifting the fleet from reactive repairs to proactive, planned interventions.
• Fleet Performance Forecasting
  • Strategic Projections: Build and refine statistical forecasts for fleet-wide availability to support long-term service agreements (LTSA) and financial risk management.
  • Scenario Simulation: Model the impact of proposed fleet retrofits and corrective actions to forecast the expected "lift" in availability before capital is deployed.
  • Growth Forecasting: Develop reliability expectations for next-generation turbine designs, ensuring that "as-shipped" products meet rigorous customer production guarantees.

Qualifications

• Bachelor’s degree in Mechanical Engineering, Electrical Engineering, or a related computational field (e.g., Systems Engineering or Data Science with an engineering focus).
• Strong foundation in probability and statistics.

Skills

• Experience in Python, JMP/JSL, R, or SQL for engineering applications and data automation (highly preferred).
• Proven experience in reliability modeling, life-cycle analysis, or predictive performance forecasting for heavy-duty industrial assets.
• Ability to summarize complex technical data into clear, actionable conclusions for stakeholders across a global organization.
• At least 6 months of experience