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PacifiCorp

Energy Supply Data Scientist

Pay: $130,000–$170,000/yr

Posted: 1 week ago

Location: Portland, OR (Onsite)

Last Updated: 1 week ago

Hours: Full-Time

Expires: 10/9/2026

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What they do

A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.

$116,813 / year median in Oregon

+17% projected growth

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Job Description

Energy Supply Data Scientist Date Posted:

5 September 2026

Closing Date:

October 5, 2026

Recruiter:

PacifiCorp Location:

Portland, Oregon Salary:

USD130,000

USD170,000

Job Type & Industry:

Data, Ai & Technology >

Data Science, Energy, Utilities & Mining Contract Type:

Permanent Job Reference:

2957360970-2 Apply for this job now Job Description PacifiCorp seeks an Energy Supply Data Scientist to optimize power supply decisions across our western U.S. utility operations. In this role, you will build and deploy statistical and machine learning models to forecast load, renewables and market prices, support unit commitment and dispatch, and analyze fuel and hedging strategies. You will work closely with trading, resource planning and grid operations teams to turn complex operational and market data into actionable insights that improve reliability, reduce costs and support our transition to a cleaner, more resilient grid. Responsibilities Develop and maintain forecasting models for load, renewable generation and market prices Analyze power supply portfolios, fuel strategies and hedging performance Support unit commitment, dispatch and trading decisions with data-driven insights Design and implement robust data pipelines and analytics workflows Create dashboards and visualizations for trading, operations and planning teams Collaborate with cross-functional stakeholders in a regulated utility environment Evaluate impacts of renewable integration and grid modernization initiatives Document models, methods and assumptions to meet regulatory and audit standards Required Skills Python RSQLMachine learning modeling Time-series forecasting Power/energy market analysis Data visualization (e.g., Tableau, Power BI) Statistical analysis ETL and data pipeline tools Cloud analytics platforms