Fuels and Fleet or Senior Fuels and Fleet Reliability Analyst: Power Generation Business Analysis

Duke Energy Corporation•Charlotte, NC

4d•Hybrid

About The Position

This position provides analytical support for fuel procurement and power generation trading and dispatch models used in the economic planning and operation of Duke Energy’s $6B multi-commodity fuel and power portfolio and 50 GW+ regulated thermal and renewable generation fleet. The role focuses on quantifying generation portfolio reliability, forecasting fuel requirements, evaluating renewable energy impacts, optimizing battery storage economics, and supporting outage scheduling with production cost models. Depending on the successful applicant’s qualifications, the hiring manager may fill the position at a higher or lower level in the job hierarchy. The analyst defines and updates model inputs, runs stochastic and reliability models, and presents findings to technical and business audiences. The position works with internal stakeholders and industry groups, improves model efficiency and accuracy, and conducts analyses for outage scheduling, deal evaluation, scenario planning, and renewable technology integration. It also creates visualizations and authors technical documents and white papers, contributing to regulatory filings and testimony. The role is hybrid after onboarding, with work performed remotely and onsite. Hybrid employees must live within a reasonable commute—no more than 50 miles one way—from the designated Duke Energy facility and are expected to work onsite an average of three full workdays per regular workweek, as required and directed by their manager. The work takes place in a highly collaborative office environment. Travel is 5–15%.

Requirements

Analyst level: Bachelor’s degree in Business, Engineering, Accounting, Data Science, or another related degree; alternatively, High School/GED and at least four years of related work experience.
Senior level: Bachelor’s degree in Business, Engineering, Accounting, Data Science, or another related degree, plus at least five years of related work experience; alternatively, High School/GED and at least nine years of related work experience.
Must possess all basic/required qualifications to be considered.
Must be able to work lawfully in the U.S. without employment-based immigration sponsorship, now or in the future.

Nice To Haves

Master’s degree in Business, Engineering, Accounting, Data Science, or another related degree.
High proficiency with Excel and data visualization tools such as Power BI or QlikView.
Excellent communication and presentation skills, including the ability to communicate technical subjects to a wide range of audiences.
Experience with reliability and resource adequacy modeling, including loss of load, capacity accreditation, reserve margin, and ancillary reserves.
Programming skills in data science or mathematical software packages, and/or interest in Python or Matlab.
General understanding of the electric, gas, oil, or coal industries.
Experience with mathematical optimization techniques and production cost models such as SERVM and PowerSimm.
Understanding of probability distributions, stochastic processes, and tail risk estimation.
Practical experience managing data in traditional databases (Oracle, SQL Server) and/or cloud databases (AWS), including creating tables and views and querying large databases.

Responsibilities

Define and update key inputs for production cost models; run stochastic and reliability models; summarize and present results to technical and business audiences.
Conduct reliability analysis, including resource adequacy, ELCC, LOLH, solar integration service charge (SISC), and screening operating reserve studies.
Build and maintain relationships with stakeholders across Fuels & System Optimization, Resource Planning, Engineering, Rates, Financial Planning, Wholesale, Environmental, and Accounting teams.
Engage with resource adequacy industry working groups and advise and advocate for the company as applicable.
Identify and implement process improvements to enhance model efficiency and accuracy; evaluate model performance by comparing forecasts to actuals.
Conduct ad hoc analyses supporting outage scheduling, deal evaluation, scenario planning, and renewable energy technology integration.
Create tools and visualizations to communicate changes in model inputs and outputs.
Author technical documents and white papers for internal and external audiences; contribute to regulatory filings and testimony.