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Energy Analyst II | Quantitative Analyst - Energy Markets | remote (US)

Work from home Full-time role Hiring

Location : Preference is given to candidates who can work in Denver, Colorado. However, we are also open to candidates based in Texas, Illinois, and Massachusetts. Position Type: Full-time, Permanent Industry: Commodities & Energy analytics Report To : Manager of Analytics

About Us

Founded in 1995, Zema Global Data Corporation empowers organizations to simplify complexity, reduce risk, and make faster, more confident decisions that drive measurable results. Over the past two years, Zema Global has accelerated its growth through strategic investment and acquisition to strengthen our global leadership. Together we’re helping our customers gain a Decisioning Advantage – one bold idea at a time. With a presence across global energy, commodity, and financial markets, Zema Global empowers customers to simplify complexity, reduce risk, and make faster, more confident decisions that drive measurable results. At Zema Global, we Think Big, Make It Happen, and Win as One. We thrive on collaboration, creativity, and respect, united by a shared drive to innovate and deliver meaningful impact for our customers and communities. If you’re inspired by solving complex challenges and contributing to a culture that values purpose and performance, we invite you to join us. About The Role cQuant is seeking an Energy Analyst II to assist with software implementations, ongoing customer support, and maintenance/enhancements related to the analytical models within its web-based energy analytics platform. The Energy Analyst II will interface directly with cQuant’s users, helping to instill best practices in quantitative modeling for portfolios amid the energy transition and enabling these users to realize maximum value from the cQuant solution. The Energy Analyst II will also work closely with various other departments within cQuant, including sales and marketing, quantitative development, and platform software, to assist in development, validation, quality assurance, and documentation of new energy-focused analytical products and features. The direct client-facing nature of the role will require the successful candidate to demonstrate both strong technical and problem solving abilities as well as excellent written and verbal communication skills. If you are passionate about the energy industry and want to be at the forefront of the quantitative analytics enabling the energy transition, we want to hear from you! Job Responsibilities

  • Configuring, calibrating, and validating cQuant’s analytical models within implementation projects and/or ad hoc engagements.
  • “Wrangling” energy and financial data.
  • Providing direct analytical support to existing and/or prospective clients.
  • Troubleshooting/debugging software failures.
  • Developing reporting dashboards and visualizations for integration into cQuant’s production software.
  • Writing documentation for existing analytical functionality.
  • Training cQuant users on existing functionality and best practices.
  • Performing testing and QA of cQuant’s models and analytical feature enhancements.
  • Implementing automated error checks and data validation for existing models.
  • Generating client-facing reports in R or Microsoft Excel.

Required Skills And Knowledge The successful candidate will be highly self-motivated and work well within a close-knit and dynamic team of bright and driven analytical software professionals. Work is fast-paced and results oriented, with little room for error or re-work, and the ideal candidate will excel in this environment. Must-Have Qualifications & Skills

  • Master’s degree in a quantitative discipline (Mathematics, Applied Mathematics, Statistics, Physics, Economics/Quantitative Economics or other) or a Bachelor’s degree along with 2+ years of relevant wholesale electric power industry experience in a quantitative role.
  • Less than 3 years of relevant work experience (entry-level role).
  • Strong grasp of statistics and time series analysis (probability distributions, regression models, stochastic processes).
  • Python/R proficiency (4+ years including academic experience) for data analysis and model development.
  • Excellent written and verbal communication skills; ability to explain complex technical concepts to clients.
  • Hands-on experience in configuring, calibrating, and validating analytical models.
  • Experience handling large datasets, reporting, and visualization development.
  • Strong problem-solving skills, attention to detail, and proactive mindset.
  • Self-motivated, highly organized, and able to work in a fast-paced, results-oriented environment.

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