TL;DR
Senior Data Scientist (Data Science/ML): Developing AI-native capabilities and advanced forecasting models for energy and natural resources analytics with an accent on cross-domain AI systems, knowledge-graph analytics, and strategic investment decision support. Focus on building scalable machine learning models, encoding domain knowledge, and collaborating across product, data, and engineering teams to drive AI solutions in a hybrid work environment.
Location: Hybrid in Edinburgh or London, United Kingdom
Company
Wood Mackenzie is a global leader in analytics, insights, and proprietary data across the energy and natural resources sectors, with a team of 2,700 experts in 30 countries.
What you will do
- Build machine learning and forecasting models for scenario analysis and energy transition planning
- Encode domain knowledge into machine-readable structures enabling causal reasoning
- Analyze large-scale, high-dimensional datasets across commodities and markets
- Collaborate with engineers to design scalable data pipelines and deploy models
- Support consulting engagements with analytical models and simulations
- Validate and iteratively improve models with product and research teams
Requirements
- Must be able to work hybrid from Edinburgh or London offices
- 5+ years experience in machine learning or statistical modelling
- Strong Python and ML libraries experience (scikit-learn, PyTorch, XGBoost)
- Experience with complex, multi-domain datasets and cross-functional teamwork
- Strong analytical and problem-solving skills
Nice to have
- Knowledge of energy markets or asset modelling
- Consulting or client-facing analysis experience
Culture & Benefits
- Inclusive and trusting work environment with customer commitment
- Flexible working to accommodate global time zones
- Hybrid work model requiring office presence at least two days per week
- Focus on accelerating change and curiosity-driven innovation