Senior Forecasting Analyst at MGE Energy in Madison, WI

  • Company: MGE Energy
  • Location: Madison, Wisconsin
  • Job type: full time
  • Workplace: hybrid
  • Posted: 2026-09-18

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Job description

Job Purpose Madison Gas and Electric is seeking a Senior Forecasting Analyst to support and continuously improve electric and natural gas sales, customer, revenue, and peak-demand forecasting. In this senior-level individual contributor role, you will apply advanced statistical modeling, financial analysis, and business insight to develop defensible forecasts that support budgeting, regulatory analysis, resource planning, and long-range decision-making. This is an opportunity to translate complex data into clear, actionable recommendations for senior leaders and cross-functional partners while helping shape critical planning decisions for a reliable, forward-looking energy company. Core Responsibilities Note: This list is not all-inclusive Develop, maintain, and enhance short- and long-term forecasts of electric and natural gas sales, customer counts, and operating revenue by customer class, rate category, or other relevant business segments. Apply statistical and analytical techniques such as regression, time-series analysis, weather normalization, trend analysis, segmentation, sensitivity analysis, and forecast error measurement to evaluate historical results and projected outcomes. Analyze customer billing, usage, weather, economic, rate, and operational data to identify underlying trends, structural changes, risks, and key drivers of revenue and sales. Integrate forecast outputs with budgets, long-range financial plans, regulatory analyses, resource planning assumptions, and other enterprise planning processes. Perform actual-to-forecast variance analysis and clearly explain the effects of weather, customer growth, usage patterns, rates, economic conditions, and other business factors. Design and maintain repeatable forecasting processes, analytical datasets, dashboards, and reporting tools that improve accuracy, efficiency, transparency, and control. Develop scenarios and sensitivities to evaluate uncertainty and the financial implications of alternative weather, economic, customer, rate, and market assumptions. Validate models and data through back-testing, reasonableness checks, reconciliation, peer review, and ongoing monitoring of forecast performance. Partner with business and technical teams to define data requirements, resolve data-quality issues, and improve access to reliable, well-governed information. Communicate assumptions, methodologies, results, limitations, and recommendations in a clear manner for technical and non-technical audiences, including senior management. Maintain comprehensive documentation of data sources, model logic, assumptions, controls, changes, and forecast decisions to support continuity, review, and auditability. Monitor relevant utility, customer, technology, and economic developments and assess their potential implications for electric and natural gas sales and revenue forecasts. Provide analytical leadership, support continuous improvement, and serve as a subject matter resource for revenue and sales forecasting. Behavioral Competencies Business Acumen – Connects analytical results to utility operations, financial performance, customer behavior, regulatory considerations, and other business decisions. Analytical Judgment – Selects appropriate methods, tests assumptions, recognizes limitations, and balances model output with informed business judgment. Strategic Thinking – Anticipates emerging trends and develops forward-looking insights that support long-term planning. Communication – Explains complex analyses, uncertainty, and recommendations clearly and concisely for the intended audience. Collaboration – Builds effective relationships across functions and incorporates diverse operational and technical perspectives. Ownership and Accountability – Delivers accurate, timely work; maintains strong controls and documentation; and follows issues through resolution. Continuous Improvement – Identifies practical opportunities to improve forecast quality, process efficiency, data reliabili

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