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
Job Description
The Principal Data Scientist will play a pivotal leadership role in building AI-native capabilities for both Synoptic, Wood Mackenzie’s AI-first innovation unit, and the broader Energy & Natural Resources consulting portfolio. This role will be a leader in the development of cross-domain AI systems, knowledge-graph–powered analytics, and advanced forecasting models that support high-impact commercial workflows such as portfolio scenario analysis, M&A intelligence, forecasting, and energy transition planning. The Principal Data Scientist will also provide technical leadership across consulting engagements, shaping solutions to achieve our mission to transform the way we power our planet.
Main responsibilities
Working in the central machine learning department, you will be collaborating with our product, data, research, modelling, data science and engineering teams and reporting to the head of Applied AI. You will drive revenue growth by expanding our capabilities, assets and end-to-end AI solutions.
Responsibilities will include:
- Lead design and development of AI-native systems leveraging domain-specific ontologies, knowledge graphs, network models, and agentic reasoning frameworks
- Provide technical oversight across multiple projects, ensuring modelling approaches align with high-value client workflows
- Work closely with embedded SMEs to encode domain knowledge into machine-readable structures that enable causal reasoning across global energy systems
- Collaborate with cross-functional engineering teams to deploy scalable pipelines integrating data from upstream, LNG, power, renewables, carbon, metals, and macroeconomic domains
- Serve as the primary AI technical authority for consulting engagements, shaping proposal design, analytical methodologies, and delivery quality
- Mentor senior and mid-level data scientists, establish modelling standards, and define best practices for reproducibility, evaluation, and model governance
- Engage with clients to understand strategic decision workflows and translate them into AI-driven analytical products.
- Partner with product, research, and data engineering teams to ensure Synoptic outputs can scale into commercial products.
We are a hybrid working company and the successful applicant will be expected to be present in the office at least two days per week to foster and contribute to a collaborative environment, but this may be subject to change in the future.
Due to the global nature of the team, a degree of flexible working will be required to accommodate different time zones.
Key Skills & Experience
You will be passionate about solving complex customer problems and bringing great products to market.
Essential Skills
- Significant experience delivering advanced machine learning, graph-based modelling, or AI systems in production
- Expertise in ontology design, structural modelling, or knowledge graphs applied to complex, interconnected domains
- Demonstrated ability to lead multi-disciplinary analytical teams
- Experience working on consulting or client-facing analytics projects with executive stakeholders
- Proven ability to design modelling architectures that scale from prototype to product.
- Advanced proficiency in Python, ML frameworks, and cloud-native pipelines
- Excellent communication skills, including the ability to articulate complex models to both technical and commercial audiences
Preferred Skills
- Strong understanding of energy systems, cross-commodity interactions, or large-scale optimisation and forecasting
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.
