Principal Optimization Engineer

Join the Market Leader in Electric Power Data and Analytics Solutions

The electrical grid is the largest and most complicated machine ever built. Yes Energy’s industry-leading electric power trading analytics software provides real-time visibility into the massive amount of data generated by the North American electrical grid daily. Our unique and innovative view of the data informs real-time trading decisions and mid-to-long‑term investment decisions that keep utility prices low, support the energy transition, and keep the grid running.

It’s both challenging work and work with a purpose.

Be a part of our successful, growing business during international transformation.

As a Principal Optimization Engineer, you will collaborate with leaders in technology, data, and energy to build solutions and tools for handling the highly complex problems posed by the evolving power grid. You will be writing interactive software to analyze and explore energy data, including building new modeling constraints and optimization model formulations. We are curious people who take pride in our work, value high‑quality communication, and strive to improve continuously.

• Salary range: $170,000 - $190,000
• Location:
  
  Yes Energy’s core offices - Boulder, CO;
  Chicago, IL;
  Boston, MA; or Richmond, VA
• Full‑time
• Hybrid - 2 days a week in the office
• Reporting to:
  Senior Director, Engineering

• Develop, test, deploy, and maintain scalable, reliable software using our backend platform and technologies.
• Model and develop new constraints for the Mixed Integer Program (MIP)
• Analyze, evaluate, and optimize the MIP solver runtime in different scenarios
• Work closely with operations and infrastructure to build and scale services
• Participate in all product life cycle phases: requirements analysis, design, development, deployment, and support.
• Embrace Agile development methodologies and practices.
• Contribute to implementation and architecture discussions.
• Coach, mentor, and guide peers, driving an excellence and continuous learning culture

• Minimum of 8 years of experience working as an optimization engineer
• Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field, or related years of experience
• Proficiency in C# or similar language
• Must have advanced skills in modeling linear and integer optimization models.
• Advanced mathematical skills required.
• Passion for optimizing system performance and scalability.
• Familiarity with Agile development methodologies.
• Excellent communication and teamwork skills. Passion for sharing knowledge with the rest of your team, building shared tooling, and directly helping customers.
• Self‑directed and comfortable supporting the needs of multiple teams, systems, and products.
• Continual learner, engaged in professional development.

• A Master’s degree or higher in Mathematics, Industrial Engineering, Data Science, or Electrical Engineering
• Have experience with CPLEX, Xpress, or Gurobi
• Have a desire to learn the energy industry or expertise in power system modeling

C#, Data Science, Mixed Integer Programming (MIP), Linear Programming (LP), Gurobi, CPLEX, Xpress, Model Optimization, Agile, TDD / Test‑Driven Development

At Yes Energy, we value connecting directly with candidates. We kindly ask that third‑party recruiters and agencies not submit resumes, as we are not open to external recruiting partnerships.

Yes Energy delivers real‑time market data and electric power trading decision solutions. Over 1,000 market participants use Yes Energy solutions daily. The business is a leader in all aspects of information content collection and management, developing and delivering data and market analytics solutions. Since its inception in 2008, Yes Energy has become a trusted and respected supplier of innovative and reliable solutions focused on the needs of power market analysts, traders, and trade managers.

Yes Energy has a team of over 350 amazing professionals in Boulder, CO (HQ);
Boston, MA;
Chicago, IL;
Glendora, CA;
Richmond, VA;
London, United Kingdom;
Auckland, New…