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

Duke Energy•Charlotte, NC

2d•Hybrid

About The Position

This position provides analytical support for fuel procurement and power generation trading and dispatch models used to support 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. Key areas include quantifying generation portfolio reliability, forecasting fuel requirements, evaluating renewable impacts, optimizing battery-storage economics, and supporting outage scheduling through production cost models. The role defines and updates model inputs, runs stochastic and reliability models, and communicates results to technical and business audiences. It works with stakeholders across multiple internal functions and participates in resource adequacy industry working groups. The position also improves model processes and accuracy, compares forecasts with actual results, conducts ad hoc analyses, creates visualizations, and prepares technical documents, white papers, regulatory filings, and testimony. The position may be filled at a higher or lower level in the job hierarchy depending on the successful applicant’s qualifications. Work is hybrid after onboarding, with employees expected to work from their assigned Duke Energy facility an average of three full workdays per regular workweek and live within a reasonable commute of no more than 50 miles one way. Travel is 5–15%.

Requirements

Analyst level: Bachelor’s degree in Business, Engineering, Accounting, Data Science, or another related degree; alternatively, a high school diploma/GED and four or more years of related work experience.
Senior level: Bachelor’s degree in Business, Engineering, Accounting, Data Science, or another related degree, plus five or more years of related work experience.
Senior level alternative: High school diploma/GED and nine or more years of related work experience.
Ability 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 and QlikView.
Excellent communication and presentation skills, including the ability to explain 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 such as Oracle or SQL Server and/or cloud databases such as AWS.
Ability to create tables and views and query 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 analyses, 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 integration of renewable energy technologies.
Create tools and visualizations that clearly communicate changes in model inputs and outputs.
Author technical documents and white papers for internal and external audiences.
Contribute to regulatory filings and testimony.