Grid Optimization Specialist

As a Grid Optimization Specialist , you will leverage artificial intelligence, machine learning, and advanced analytics to enhance grid efficiency, reliability, and sustainability. Your work will involve optimizing energy distribution, predicting demand, and ensuring system resilience, directly contributing to a more stable and sustainable power grid.

Responsibilities

• Develop and implement AI and machine learning models to optimize energy distribution and grid stability.
• Analyze and model data from grid systems to forecast demand, prevent outages, and support load balancing.
• Use predictive analytics for real-time grid monitoring, addressing energy consumption spikes, and optimizing resource allocation.
• Collaborate with engineers and data scientists to deploy data-driven solutions for grid management and efficiency.
• Work with smart grid technologies and IoT data to monitor infrastructure performance and optimize energy flow.
• Conduct research on new AI applications to address grid challenges, such as renewable integration and peak load management.
• Prepare and present analytical findings and optimization strategies to technical teams and management.

Required Qualifications

• Education : Bachelors degree in Electrical Engineering, Data Science, Computer Science, or a related field (Masters or Ph.D. preferred).
• Experience : 3+ years of experience in power systems, data science, or machine learning, with a focus on energy or utilities.
• Technical Skills :
  • Proficiency in Python, R, and machine learning libraries (e.g., TensorFlow, PyTorch).
  • Knowledge of power systems, smart grids, and renewable energy integration.
  • Experience with time-series analysis, statistical modeling, and optimization techniques.
  • Familiarity with big data platforms (e.g., Spark, Hadoop) and cloud computing (e.g., AWS, Google Cloud).
• Domain Knowledge : Understanding of grid operations, load balancing, and predictive maintenance in energy systems.

Preferred Skills

• Experience with real-time data processing and IoT integration for grid monitoring.
• Knowledge of energy policies, sustainability practices, and renewable energy systems.
• Familiarity with reinforcement learning or other advanced AI techniques applied to grid optimization.
• Strong communication skills to explain technical solutions to non-technical stakeholders.