Internship Quantitative Risk Modeler Jobs in Texas

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Position Summary

The Quantitative Analyst in the Wholesale Risk Analytics team will support NRG's risk generation forecasting, and analytical processes across the wholesale portfolio. This role is highly analytical and business focused, with responsibility for developing, maintaining, and enhancing models that support accurate forecasting and insights. The position offers significant visibility across the organization and requires close collaboration with Commercial Operations, Financial Planning, Asset Management, and Senior Leadership.

Essential Responsibilities

        Operate and enhance NRG's wholesale gross margin forecasting models, including annual budget forecasts and monthly reforecasts.

        Maintain and improve daily mid to longterm forecasting models used for commercial operations position reporting.

        Apply data-driven techniques and pattern-recognition methods to improve forecast accuracy, identify anomalies, and streamline analytical workflows.

        Build and automate data pipelines, reporting tools, and model processes using Python, SQL, and Excel/VBA.

        Support adhoc analytical requests from Senior Management, Finance, Market Operations, Plant Operations, and Asset Management.

        Partner with IT to implement model improvements, enhance data quality, and modernize analytical infrastructure.

        Contribute to valuation analysis, scenario modeling, and risk analytics supporting commercial decisionmaking.

        Prepare clear, concise presentations and analysis for leadership discussions, investment reviews, and risk reporting.

Required Skills & Experience

        Bachelor's degree in economics, Finance, Engineering, Computer Science, Mathematics, Statistics, Operations Research, or a related field.

        Strong proficiency in Microsoft Excel, including advanced formulas, VBA, and data manipulation.

        Handson experience with Python and SQL for data analysis, automation, and model development.

        Solid understanding of statistical modeling, forecasting techniques, and quantitative analysis.

        Strong written and verbal communication skills.

        High attention to detail and commitment to producing accurate, highquality work.

        Selfstarter with the ability to manage multiple priorities in a fastpaced environment.

Preferred Qualifications

        Three or more years of experience in the U.S. power markets, merchant generation, or energy trading environments.

        Familiarity with power market simulation or production cost modeling tools such as PROSYM, PROMOD, GenTrader, or Aurora.

        Experience with longterm asset modeling, dispatch modeling, or valuation of generation assets.

        Exposure to machinelearning methods and AIassisted analytical tools.

        Experience working with large datasets or cloudbased analytics environments.

        Prior experience in energy market consulting or risk analytics roles.

Working Conditions

        Hybrid work schedule with 4 days per week in the Princeton office.

        Open office environment with frequent crossfunctional interaction.

        Occasional overtime may be required to meet deadlines or support special projects.

        Fastpaced environment requiring adaptability and strong problemsolving skills.

Compensation

The base salary range for this position is: $85,600-$105,400.  Actual salaries will vary based on factors including location, experience, and performance. Total compensation may include annual bonuses, short and longterm incentives, and programspecific awards. The position may also be eligible for NRG's benefits program, including medical, dental, vision, 401(k), and flexible spending accounts.

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.