Senior/Principal Quantitative Risk Analyst

At PGE, our work involves dreaming about, planning for, and realizing a smarter, cleaner, more enduring Oregon neighborhood. Its core to our DNA and we haven’t stopped since we started in 1888. We energize lives, strengthen communities and drive advancements in energy that promote social, economic and environmental progress. We’re always on the lookout for people passionate about leading and being a part of teams that are advancing innovative clean energy solutions that are also affordable and accessible to all.

Summary

PGE seeks a talented quantitative analyst with energy analytics and modeling experience to support PGE Energy Supply, Trading Analytics. The Senior/Principal Quantitative Risk Analyst takes a leadership role in communicating data-informed strategy and reports to the Manager, Market Fundamentals and Trading Analytics in Power Operations.

This role is ideal for a candidate who thrives in a fast-paced trading environment, has a strong technical background, is comfortable building and automating data solutions from scratch, and has curiosity and passion about the electric utility business. The ideal candidate is resourceful and capable of quickly turning market insights into actionable tools for traders and leadership.

Key Responsibilities

Business Partnership and Thought Leadership   Supports senior leadership and key business partners in navigating uncertainty in an increasingly complex, data-driven energy landscape. Applies quantitative insights and analytics tools to enhance decision-making in trading, hedging, and portfolio management. Collaborates across teams to foster transparency and efficiency in portfolio analysis.

Quantitative Modeling and Portfolio Risk Optimization Develops and maintains risk models and valuation frameworks for structured products, generation assets, and portfolio hedging strategies. Leverages statistical techniques (VaR, GMaR, stress testing, backcasting) to enhance models, providing traders and portfolio managers with insights for market decisions.

Data Engineering and Automation  Independently sources, integrates, and structures internal and external datasets to support analytics and decision-making. Builds and maintains custom data pipelines and automated workflows, ensuring data accessibility for trading and leadership teams. 

Data Visualization & Communication Develops and maintains Tableau dashboards and automated reporting tools to ensure quantitative insights are accessible for diverse audiences.  Translates complex modeling results into clear, interactive visuals, enhancing transparency and decision-making across the organization.

Education/Experience/Certifications

Education Requires a bachelor’s degree in computer science, electrical engineering, economics or other related field or equivalent experience. MSc or PhD in mathematics, statistics or computer science or related field, such as physics, economics or operations research preferred.

Experience Typically 12 or more years in data science or related field. Three or more years of experience in a quantitative role within the energy industry. Experience with wholesale power and/or commodities markets in the Western Electricity Coordinating Council footprint  is preferred.  

Certifications, Licenses and Training Advanced proficiency in SQL, Python or R, with the ability to build, automate, and optimize data workflows. Experience with data visualization tools (e.g. Tableau) preferred. Experience implementing time series analysis and Monte Carlo simulations, regression and econometric techniques, optimization techniques with commercial solvers. Familiarity with with Production Cost Modeling (Aurora, PLEXOS, GE MAPs, etc.) preferred.

Competencies (Knowledge, Skills, Abilities)

Functional Competencies:

Expert quantitative analysis skills

Expert data literacy

Advanced knowledge of multiple business processes in three or more of the following business areas: Corporate, T&D, Generation and Operations, Power Supply

Advanced ability to develop complex predictive models and represent the models using simple and advanced visualization mecha