Portfolio Strategy Analyst, Data Center Energy Responsibilities:

• Develop and maintain portfolio-level energy strategy models that assess capital and operational cost implications of data center development decisions across multiple geographies
• Analyze energy market structures, utility rate environments, and grid interconnection timelines to inform site selection and development sequencing decisions
• Synthesize load forecasting data, capacity planning inputs, and energy procurement signals to produce integrated portfolio outlooks for infrastructure leadership
• Identify strategic risks and opportunities across the data center development pipeline related to energy availability, grid constraints, and regulatory changes
• Partner with Commercial Energy and Clean Energy teams to align the energy strategy with broader infrastructure development priorities
• Build and support scalable analytical tools and dashboards to track portfolio-level energy metrics, development milestones, and cost performance against targets
• Support scenario planning and sensitivity analyses for new market entry, capacity expansion, and energy transition initiatives
• Collaborate with Finance and Infrastructure teams to evaluate the energy-related financial impacts of development decisions and support investment approvals
• Communicate portfolio strategy findings and recommendations to cross-functional stakeholders and infrastructure leadership through structured written and verbal presentations

Minimum Qualifications:

• 6 years of experience in energy strategy, infrastructure development, or portfolio planning within the energy industry, large-scale data center development, or a related capital-intensive sector
• Demonstrated ability to build integrated financial and market models that connect deal-level economics to portfolio-level outcomes
• Experience analyzing energy market data, utility rate structures, grid interconnection processes, or power procurement frameworks in the context of large infrastructure portfolios
• Hands-on experience with wholesale energy markets, including familiarity with pricing structures (LMPs, capacity markets, RECs, PPAs), basis risk, and forward curves
• Experience building and maintaining complex financial or operational models to support strategic planning and investment decision-making
• Experience working cross-functionally with Finance, Site Development, and Infrastructure teams to translate analytical outputs into actionable strategic recommendations
• Experience in communicating complex energy or infrastructure concepts clearly in written and presentation formats to technical and non-technical audiences

Preferred Qualifications:

• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience with data visualization tools to build portfolio tracking and reporting solutions
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience supporting data center, hyperscale infrastructure, or large industrial energy strategy in a portfolio planning or development context
• Experience with energy portfolio optimization or resource planning at scale (10+ gigawatts)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Familiarity with clean and renewable energy procurement structures, including power purchase agreements and renewable energy certificates, as they relate to large-scale infrastructure portfolios
• Experience in building and presenting risk frameworks that quantify exposure across multiple dimensions (market, credit, volumetric, operational)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Proficiency in SQL, Python, or similar tools for large-scale data analysis and automation of analytical workflows

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