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Wood Mackenzie

Data Associate

Posted 20 Days Ago
Be an Early Applicant
2 Locations
Entry level
2 Locations
Entry level
As a Data Associate, you will enhance data quality for power and renewables by conducting primary and secondary research, maintaining data related to power plants, and collaborating with colleagues to streamline data collection processes.
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Wood Mackenzie is the global data and analytics business for the renewables, energy, and natural resources industries. Enhanced by technology. Enriched by human intelligence. In an ever-changing world, companies and governments need reliable and actionable insight to lead the transition to a sustainable future. That’s why we cover the entire supply chain with unparalleled breadth and depth, backed by over 50 years’ experience. Our team of over 2,400 experts, operating across 30 global locations, are enabling customers’ decisions through real-time analytics, consultancy, events and thought leadership. Together, we deliver the insight they need to separate risk from opportunity and make confident decisions when it matters most.

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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

Job Description

We are looking for a Data Associate to join Wood Mackenzie’s Power and Renewables Project Tracking Data team. 

This role will focus on data collection via research.

Associates are our front line for data collection and lay the groundwork for industry leading analysis.

The candidate will work closely across our Power and Renewables teams to support coverage of the global renewable industry.

Ideal candidates are thoughtful, intellectually curious, and creative. Attention to detail and dedication to continuous process improvement are critical in this data curation focused role.

Responsibilities

  • Create, monitor, and maintain data relating to power plants by conducting primary and secondary research. Examples of targeted data include: Renewable project lists, data centers, company financials, asset transactions, tender announcements, and policy developments.
  • Evaluate the alignment of our data published sources such as regulatory agencies, market operators, and developer disclosures.
  • Collaborate with colleagues across multiple time zones and disciplines to leverage best practices and deliver according to project timelines.
  • Perform established workflows to execute data collection and improve data quality.

About You

  • Proven analytical capabilities, both qualitative and quantitative.
  • Demonstrated interest in data management and in the renewable/energy industry.
  • Excellent problem solving, documentation, communication and organization skills, and attention to detail.
  • An engaging nature, capable of connecting with co-workers, clients and industry stakeholders in a wide range of professional settings including giving presentations.
  • A deep intellectual curiosity about what drives markets based on economic principles.
  • Passionate ownership of projects and excitement to share accomplishments with fellow Woodmackers
  • Strong listening and critical thinking skills.
  • Fluency in English. Additional European language skills, and/or Arabic are a plus.
  • Comfortable working with common Excel functions and query languages.
  • You are committed to contributing to a welcoming and inclusive environment, are sensitive to diverse perspectives, and are passionate about equity in the workplace.

Equal Opportunities

We are an equal opportunities employer. This means we are committed to recruiting the best people regardless of their race, colour, religion, age, sex, national origin, disability or protected veteran status. You can find out more about your rights under the law at www.eeoc.gov 

If you are applying for a role and have a physical or mental disability, we will support you with your application or through the hiring process.  

Top Skills

Data Collection
Excel
Query Languages
Research

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