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
Role Purpose
As part of the Data team working on the delivery of data for Lens Hydrogen, the Data Associate will work on the development of costs, emissions, and other data models for the low-carbon hydrogen and derivatives market. Leveraging Wood Mackenzie’s proprietary data, models, and expertise, these models will enable modelling of real-world conditions to assess evolving trends in the hydrogen market.
The role will also require integrating models with the growing database of model parameters including policy data, cost curves, and technological efficiency curves.
There will be close-collaboration with cross-functional teams including research, product, engineering, and design to build and develop new models and to generate new datasets for Lens Hydrogen.
Main Responsibilities
- Support the development of costs, emissions, and other data models in code
- Maintain and debug code implemented in existing models and to understand cases where model logic does not hold
- Document methodologies implemented in models to support further model analysis
- Document data schemas for datasets used in cost models
- Prepare and transform datasets for models - ensuring that datasets conform to required data schemas
- Support the writing of requirements for cost model work
Knowledge and Experience
- Experience in performing data ETL – extracting, transforming and loading data for use, ensuring high levels of data quality, completeness, and integrity
- Proficiency in Python and SQL
- Experience in data cleaning and normalization
- A curiosity about the energy transition and developments in the hydrogen market
Key Competencies
- Issue identification and problem-solving
- Attention to detail
- Planning and implementation
- Efficiency-focused
- Determined and resilient
- Continuous improvement
- Creativity
- Building and maintaining relationships
- Communication
- Personal impact
- Collaboration
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.
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What We Do
In the middle of the energy transition, businesses and governments are faced with significant challenges. But the pace and scale of change mean every decision is made under mounting pressure. Now, more than ever, companies need reliable data, analytics and actionable insight. Wood Mackenzie is the leading global provider of data and analytics solutions for the renewables, energy and natural resources sectors . Wood Mackenzie’s services include data, analytics, insight, events and consultancy. A trusted partner for over 50 years, Wood Mackenzie’s team has over 2,300 experts across more than 30 global locations who cover the entire supply chain. Wood Mackenzie’s data and analytics empowers energy producers, governments and financial institutions to be confident in their investment decisions in the face of rapidly evolving markets. Part of the Veritas group.
