About the Role

Senior Energy Market Associate

This job is available in 2 locations

Category Consulting Job Id R2401655 Job Type Full time

Description

Senior Energy Market Associate

Locations:

Remote U.S.

Reston, VA

Houston, TX

Are you interested in working at the forefront of energy system transformation, tackling challenging energy market issues, and helping develop the next generation of models and methods for energy market analysis?

ICF is currently hiring a Senior Energy Market Associate to join our team. ICF is one of the leading consultancy firms in the energy and environmental sectors, with a proven track record and decades of experience working with government agencies, NGOs, utilities, investors, and developers across all areas of the energy system.

The Senior Energy Market Associate will join ICF’s team and work with clients to understand and keep pace with the rapidly changing energy markets. This position is ideal for someone looking for a challenging but rewarding work environment, doing hands-on work developing, implementing, and utilizing new models and methods for energy market analysis, while interacting with subject matter experts across ICF and with various clients, many of whom are major players in the energy sector.

As part of the role, you will:

  • Work with long-term fundamentals-based production cost models of the energy system.
  • Evaluate changes to regulations, policies, and market designs to reflect their impacts in various energy system models.
  • Lead the efforts for warehousing data from various public and internal sources, using RESTful methods and cloud services to orchestrate regular updates.
  • Design and implement new models and methodologies to capture market developments and to keep up with changing client needs and requirements.
  • Incorporate new and innovative techniques, leveraging the latest technological advancements in machine learning, artificial intelligence, and enabling them through cloud computing.
  • Communicate new developments and insights to both internal and external audiences.

Minimum qualifications:

  • Bachelors degree in operations research, applied mathematics, engineering, economics, or similar quantitative focused subject.
  • 5+years Data Analysis experience contributing to data-driven business growth.
  • Advanced experience in programming models in languages such as Python, R, etc. for data processing analytics at a distributed scale, such as with PySpark.
  • Strong ability to execute complex queries and understand Stored Procedures in SQL
  • Advanced analytical skills and capabilities and a proven track record in developing and implementing quantitative models.

Preferred qualifications:

  • A masters degree or PhD in operations research, applied mathematics, engineering, economics, or another similar quantitative focused subject.
  • Experience in managing structured and unstructured databases, optimizing for efficient query performance and storage.
  • Strong analytical skills and capabilities and a proven track record in developing and implementing quantitative models.
  • Ability to understand and work with complex technical concepts, while also being able to communicate them effectively to a non-technical audience.
  • Energy Markets experience evaluating changes to regulations, policies, and market designs to reflect impacts in various energy system models.
  • Experience with analyzing production, outage, and other risk drivers typically associated with an energy modeling system.
  • Experience in working in the Azure cloud environment, running ETL operations using DataFactory, Batch processing of data at distributed scale.
  • Market modeling approaches and tools (e.g., PROMOD, Plexos, or any other Production Cost Models.)
  • Power flow modeling tools (e.g., PSLF, PSSE, TARA etc.)
  • Experience with simulation and stochastic modeling.
  • Demonstrated experience in setting up standards or measures for quantifying risk in SCED models.
  • Strong organizational and project management skills.
  • An enthusiasm for continual learning.

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