Job Description Summary

The Fleet Systems Engineering team is seeking to fill a crucial role within the team and broader renewable energy sector; a Senior Systems Engineer focused on fleet data analytics. The engineer will focus on optimizing the performance and efficiency of wind turbine systems through the analysis of data generated by turbine systems. This role involves utilizing data analytics tools, software, and domain knowledge to extract valuable insights, identify trends, and make data-driven recommendations for improving turbine operation, maintenance, and overall energy production. The engineer collaborates with cross-functional teams to enhance the reliability and productivity of wind energy generation.

Job Description

About us
GE’s Onshore Wind business has a total installed base of more than 50,000 wind turbines in more than 35 counties, with 100+ GW of global installed capacity. We harness increased onshore wind energy potential through a broad family of turbines that are uniquely suited for a variety of wind environments, including Cypress, GE’s most powerful onshore wind turbine, and GE’s 2MW platform, which has more than 20GW installed and in operation today. We are committed to our customers’ success in wind, offering a broad portfolio of products and services that make renewables the energy of choice for a cleaner future.

Essential Responsibilities

Data Collection and Monitoring:

• Collect, clean, and preprocess data from various sources, including SCADA systems, sensors, and other monitoring equipment installed on wind turbines.
• Develop and maintain processes for real-time data collection and ensure data accuracy and integrity.

Data Analysis and Interpretation:

• Apply statistical and machine learning techniques to analyze historical and real-time data to identify performance patterns, anomalies, and trends.
• Generate actionable insights to optimize wind turbine operation, maintenance schedules, and energy production.

Performance Optimization:

• Collaborate with engineering and fleet performance management teams to identify underperforming turbines and propose solutions for enhancing their efficiency.
• Develop predictive maintenance models to reduce downtime and improve overall turbine reliability.

Reporting and Visualization:

• Create meaningful visualizations, dashboards, and reports to communicate findings and recommendations to both technical and non-technical stakeholders.
• Present data-driven insights to management and other relevant teams, contributing to strategic decision-making.

Continuous Improvement:

• Stay updated with industry advancements, best practices, and emerging technologies in data analytics and renewable energy.
• Propose and implement improvements to data analysis methodologies, tools, and processes to enhance analytical capabilities.

Cross-Functional Collaboration:

• Collaborate with other departments, including engineering, fleet performance management, manufacturing & operations, maintenance & repairs, and others to integrate data insights into operational strategies.
• Contribute to a multidisciplinary team environment to drive innovation and operational excellence.

Data Security and Compliance:

• Ensure compliance with data privacy and security regulations when handling sensitive data collected from wind turbine systems.

Required Qualifications

• Bachelor's Degree in a relevant field such as Data Science, Engineering, Renewable Energy, or a related discipline.
• Minimum of 5 years of experience

Desired Characteristics

• Master's degree in a relevant field such as Data Science, Engineering, Renewable Energy, or a related discipline
• Proven ability to work in a cross-functional and global environment.
• Excellent communication skills to effectively convey complex technical information to both technical and non-technical stakeholders.
• Strong problem-solving skills with an ability to translate data insights into actionable recommendations.
• Proficiency in data analysis tools such as Python, R, MATLAB, or similar.
• Experience with data visualization tools, such as Tableau, Power BI, or others.
• Familiarity with statistical analysis, machine learning, and predictive modeling.
• Knowledge of wind turbine systems, renewable energy concepts, and SCADA systems.

Additional Information