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Machine Learning - Aplication Development Engineer
The RPMAC monitors performance and condition of renewables, thermal, LG Terminals and battery storage assets in MCAC. The responsibility of this role is to develop performance models, data analytics, machine learning models, and artificial intelligence applications to improve assets performance, safety, reliability, and planning.
Additionally, this position will develop models to extend asset life, predict critical components failures, incorporate active commercial insights and weather forecasting for full and robust asset oversight.
Implement machine learning, artificial intelligence and applications development operation initiatives in the MCAC RPMAC.
Provide data analytics and data driven relevant information to the plants and other departments to improve assets performance, reliability, work management, investment and outage plans.
Develop, maintain, retrain and use EtaPro thermal performance and advanced pattern recognition (APRs) models with plant operational data to detect and predict changes in the operating performance of plant equipment and systems.
Perform optimization analyses of site critical components using advanced analytics tools such as GE APM, SAS, Minitab and Bluence.
Develop data driven failure prediction models for potential equipment related issues and interact with station personnel to provide recommendations in order to optimize plant equipment / systems downtime.
Monitor equipment performance and predict component health, alerting SMEs and site personnel of anomalies within those trends which could adversely affect the reliability, availability, maintainability and performance of equipment.
Support and interface with component Subject Matter Experts (SMEs) to assess equipment anomalies and develop plans to mitigate risks.
Communicate equipment anomalies to plant operations, engineering personnel and plant technical analysts in a timely manner.
Identify and classify performance associated risks to the plant, provide recommendations to mitigate these risks, and follow up to ensure resolutions are tracked through to completion.
Work with power plant staff to troubleshoot and resolve operational problems identified by the machine learning and condition monitoring models.
Use multiple data sources (operations, commercial, financial, weather, fuels, prices, etc.) with data analytics applications to create new value for AES.
Develop new asset management applications and dashboards to accelerate the RPMAC process transformation to include renewable energies.
With the support of the Digital team; design, develop, implement, commission and test major and minor changes to databases in order to improve AES analytics capabilities.
Capture and quantify savings or avoided costs to express the value of team activities.
Develop local and regional projects that involve data analytics to define new process improvement opportunities.
Bachelor’s degree in Automation, Mechanical, Electronic or Electrical Engineering
5+ years of experience in the power generation industry.
Working experience in renewable energy power plants
Working knowledge of EtaPro Advanced Pattern Recognition (APR) models
Experience with advanced analytics and other reliability or condition based software applications.
Familiarity with asset performance management programs and technology applications
Experience in Project Management
Must be proficient with various software programs and systems (e.g., MS Outlook, Word, Excel, PowerPoint, Project, Visio) as well as database use.
Experience with power plant controls and control logics.
Knowledge of wind turbine SCADAs (Vestas, GE, Nordex, Mitsubishi) is preferred
Knowledge of data system integrations and networks (Ethernet, Control Net, Device Net, Modbus, OPC)
Must be able to identify process signals from P&IDs, DCS, OPC and PI Servers.
Knowledge in SQL and Non-SQL databases is preferred.
Knowledge in analytics programming platforms like Python, R, SAS or Mathlab is preferred.
Experience in developing analytics in dashboards, Power BI Preferred.
Skills and Abilities
Must be able to concentrate and understand complicated issues and / or instructions.
Must be able to work independently with little supervision, perform in a team environment, as well as effectively communicate with others.
Must possess good problem solving and troubleshooting skills.
Ability to establish and maintain effective working relationships.
Excellent communication and management skills
Good communication in English (oral and written)
Mejoramos la vida de más de 10+ millones de personas a través de la entrega segura y confiable de energía. Uno de cada tres hogares se iluminan con nuestro trabajo.