Data Scientist, Load Forecasting

NRG Energy, Inc • Houston, TX

Company

NRG Energy, Inc

Location

Houston, TX

Type

Full Time

Job Description

As an NRG employee, we encourage you to take charge of your career and development journey. We invite you to explore exciting opportunities across our businesses. You’ll find that our dynamic work environment provides variety and challenge. Your growth is key to our ongoing success—take the lead in shaping your career development, goals and future! Job Summary NRG is seeking a Data Scientist to join our Commercial Analytics load forecasting team. This role will contribute to the development and application of statistical models and machine learning techniques to support NRG’s long- and short-term trading activities. As part of a collaborative, functionally organized data & analytics group, you will work on projects related to electricity and gas contracts, power plant operations, trading, and energy services. Your work will focus on delivering repeatable, scalable solutions that improve load forecasting performance and accuracy, as well as visualizations and executive summary reporting. If you enjoy working with data, solving problems with code, learning about energy markets, and building practical forecasting models that drive real business impact, we encourage you to apply. Essential Duties/Responsibilities: • Develop, implement, and maintain statistical and machine learning models for time-series electric load forecasting (e.g., regression, ARIMA, neural networks). • Analyze drivers of electric load, including weather patterns, load growth, and demographic and economic indicators. • Translate complex business challenges into analytical objectives and actionable insights. • Evaluate model limitations and communicate areas where predictions may be less reliable. • Collaborate with cross-functional teams to integrate analytical solutions into business processes. • Communicate technical concepts clearly to both technical and non-technical stakeholders. • Leverage tools such asPython (Pandas, Statsmodels, Scikit-learn)to build and evaluate forecasting models andSQLto explore and investigate source data. Experience withR, Stata, Matlab, SAS, or Itron’s Metrix suitemay partially substitute for Python proficiency. • Perform additional duties as assigned. Minimum Requirements: • Bachelor’s degree in a quantitative discipline (e.g., Statistics, Economics, Mathematics, Computer Science, Engineering, Operations Research). • An applicable graduate degree or two years of highly relevant experience may be substituted for the degree requirement. • Experience writing, debugging, and modifying computer code to solve problems. • A basic understanding of SQL, tabular data structures, and Matrix algebra. • Proficiency in at least one major coding language or statistical analysis platform. Additional Knowledge, Skills and Abilities: • Experience in theretail electricitysector strongly preferred; wholesale electricity experience is also valuable. • Familiarity withLinuxenvironments. • Proficiency withGitfor version control. • Experience usingDatabricksor similar big data platforms. • Ability to learn and apply new quantitative techniques quickly and appropriately. • Strong communication skills and attention to detail. • Ability to interpret analytical results, assess business implications, and present findings clearly. • Critical thinking skills to validate results before dissemination. Work Environment & Physical Requirements • This is a hybrid role: part remote and part in-office (open office environment). • Must have close visual acuity for data analysis, computer work, and reading. • Occasional overtime may be required. NRG Energy is committed to a drug and alcohol-free workplace. To the extent permitted by law and any applicable collective bargaining agreement, employees are subject to periodic random drug testing, and post-accident and reasonable suspicion drug and alcohol testing. EOE AA M/F/Vet/Disability. Level, Title and/or Salary may be adjusted based on the applicant's experience or skills. Official description on file with Talent.
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Date Posted

06/06/2025

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