Jobs · Business Development · Texas

Principal Analyst – Large Loads

Wood Mackenzie · Houston, TX · 2 wk ago
On-siteBusiness DevelopmentFull-time

About the role

Wood Mackenzie is the global leader in analytics, insights and proprietary data across the entire energy and natural resources landscape. For over 50 years our work has guided the decisions of the world’s most influential energy producers, utilities companies, financial institutions and governments. Now, with the world’s energy system more complex and interconnected than ever before, sector-specific views are no longer enough. That’s why we’ve redefined what’s possible with Intelligence Connected. By fusing our unparalleled proprietary data with the sharpest analytical minds, all supercharged by Synoptic AI, we deliver a clear, interconnected view of the entire value chain. Our trusted team of 2,700 experts across 30 countries breaks siloes and connects industries, markets and regions across the globe. This empowers our customers to identify risk sooner, spot opportunities faster and recalibrate strategy with confidence – whether planning days, weeks, months or decades ahead. Wood Mackenzie Intelligence Connected WoodMac.com Wood Mackenzie Brand Video Wood Mackenzie Values Inclusive – we succeed together Trusting – we choose to trust each other Customer committed – we put customers at the heart of our decisions Future Focused – we accelerate change Curious – we turn knowledge into action

Responsibilities

  • Author research reports and one-off insights (regulatory changes, market insights, technology advancements) and contribute to the long-term demand forecast assumptions.
  • Serve as subject matter expert on data center technology, policy, siting, and energy supply for large loads; provide authoritative technical and market context to product and data teams.
  • Serve as the team’s go-to expert on AI infrastructure – compute trends, DC vs. AC power architecture, and the factors driving data center demand – informing both research and product.
  • Participate in customer and client conversations to gather feedback, use cases, and data requirements; represent Wood Mackenzie research in these product-facing conversations.
  • Guide and QA the work of data analysts and data scientists in classifying, extracting, and vetting large-load data from documents and other sources.
  • Support Sales and Marketing in existing or new client conversations/presentations and internal webinars.
  • Represent Wood Mackenzie at client meetings, conferences, and other Wood Mackenzie offices as needed.
  • Support Wood Mackenzie's consulting team on large load-related engagements as needed.

Qualifications

  • Demonstrated expertise in AI infrastructure: compute (chip types, training vs. inference workloads, and how compute demand translates into power and siting requirements), the distinction between DC and AC power infrastructure within data center design, and the technical, commercial, and policy factors driving data center demand growth.
  • 7+ years of industry or research experience in the power sector, with substantial, recent, hands-on exposure to data centers or other large electricity loads.
  • A track record of authoring research or client-facing analysis (reports, forecasts, or similar).
  • Demonstrated experience translating market or customer needs into product or data requirements, ideally through direct client- or stakeholder-facing work.
  • Comfort partnering with product, data science, or other non-research teams in ongoing, iterative workflows (standups, refinement sessions, and similar).
  • A Bachelor's or Master's degree, preferably in engineering, energy, economics, finance, or policy.
  • Excellent written and oral communication skills; ability to represent Wood Mackenzie externally with clients and at conferences.
  • Strong organizational and project management skills — able to drive forward a workstream with multiple collaborators and moving parts.
  • Ability to leverage AI tools for efficiency without compromising the correctness of the final data or product deliverables.

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