Woodmac

Woodmac

Research Analyst - Large Loads (Data Centers and Industrial Demand)

Boston, US

Sponsorship not specified$90k-$100kDetected 21 days ago
PythonData ScienceProject ManagementResearchLeadershipCommunicationPublic SpeakingOrganizational Skills

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.

Responsibilities

  • Drive and contribute to the development of AI-enabled data gathering tools, including by identifying and vetting new data sources, and supporting data science teams in classifying and extracting data from documents
  • Support Wood Mackenzie clients upon request and assist with customer acquisition and retention
  • Support Wood Mackenzie's consulting team on large load-related engagements
  • Willingness to dive into any task that needs doing in a project, whether hands-on data gathering, parsing dense regulatory documents, or guiding and QAing the efforts of data analysts
  • The analyst will support our research and product development on large electric loads, including data centres, advanced manufacturing, and facility electrification.
  • Excellent organizational skills, able to drive forward a project with many collaborators and moving parts, leveraging process tools and best practices
  • The analyst will also closely support the development of AI and data tools through which large load data is sourced and delivered to clients.
  • The analyst should have experience in project management, demonstrating skills to drive projects involving multiple teams and concurrent workflows.

Requirements

  • 3+ years of industry or research experience in the power sector or an adjacent industry
  • The knowledge base and ability to quickly gain expertise in the financial, policy, technology, and energy dimensions of large loads, particularly data centers
  • A Bachelor's or a Master's degree, preferably in engineering, energy, economics, finance, or policy
  • Ability to leverage AI tools for efficiency while not compromising on correctness of the final product
  • Excellent written and oral communication skills in English, with the ability to articulate key takeaways and craft compelling data-driven visuals
  • Experience or comfort working alongside product, data, or other non-research internal teams
  • Experience in the data center or power generation development industry
  • Experience as a research analyst, with a track record of publications and presentations
  • You can find out more about your rights under the law at www.eeoc.gov
  • Experience within the data centre industry is not required, but recent experience with respect to the technological, financial, or commodity side of the power sector is expected.

Compensation

  • The salary range for this position is $90K - $100K, which represents base pay only and does not include short-term incentive compensation or commission.

Benefits

  • Clear communication skills and ability to work independently, self-direct, and stay flexible

Company info

  • Contribute to teamwide research insights and deliver individual reports, from content development to practical client recommendations - with this part of the role expanding over time as product needs stabilise
  • Customer committed - we put customers at the heart of our decisions
  • We are looking for a Research Analyst to join Wood Mackenzie's Power & Renewables group, reporting to a Principal Analyst on the team.
  • Our research and thought leadership inform the strategies of key players throughout the energy industry, driving innovative business models while hastening the energy transition.

This listing is sourced directly from Woodmac's careers page and normalized into a canonical job model.