.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 ValuesInclusive – we succeed togetherTrusting – we choose to trust each otherCustomer committed – we put customers at the heart of our decisionsFuture Focused – we accelerate changeCurious – we turn knowledge into actionRole PurposeThe Supply Chain Market Intelligence Group (MIG) is a team responsible for managing the market insights delivered through our suite of software-as-a-service products, including price benchmarking, cost escalation, forecasting, renewable asset cost estimating, commodity exposure, supply chain risks, carbon (GHG) emissions, supplier and other category insights across all goods and services procured globally by the energy and natural resource industry. Our clients primarily leverage these insights to identify opportunities to save money and reduce risks. We are a hybrid group that wears many hats: data analyst, consultant, economist, market researcher and product owner. In our hybrid role, we collaborate closely with many teams in the company, including product development, data science, research groups, consulting, sales & marketing and customer success, among others.In particular, this role will focus on Supplier Diversity, Carbon Emissions, Risk, and other supplier and category insights within MIG.Main ResponsibilitiesPerform data extraction, manipulation, cleaning, analysis and QA of large datasetsManipulate existing data in new ways. Cleanse and enrich data to make it more powerful