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Spend Data Analyst
hace 2 días
Join to apply for the Spend Data Analyst role at Wood Mackenzie 1 week ago Be among the first 25 applicants Join to apply for the Spend Data Analyst role at Wood Mackenzie 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.
WoodMac.comWood Mackenzie Brand VideoWood Mackenzie ValuesInclusive – 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 Does your perfect day consist of cleansing, researching, and enriching complex data for customers to find useful insights and connections? Do you have a passion for slicing-and-dicing data?
Would you like to categorize and classify data to make it more usable for our customers? Do you enjoy working in a collaborative environment where you are constantly learning?
Wood Mackenzie Supply Chain is seeking a Spend Data Analyst to join our team to provide cutting edge intelligence for supply chain organizations in the energy industry. We are looking for a team player who thrives in an agile and dynamic environment, and wants to enrich data to deliver superior customer results.
As a Spend Data Analyst within Wood Mackenzie Supply Chain’s Spend Intelligence Group you will use your keen eye for detail, your creative analytical skills, and your love for working in a team to help Wood Mackenzie maintain its leadership position in energy information. The Spend Data Analyst is a key member of the Spend Intelligence Group, responsible for the data aggregation, normalization, classification and enhancement process which turns raw customer spend data into Spend Intelligence.
The analyst will utilize robust technology tools and energy industry knowledge to create a truly unique product that is critical to Wood Mackenzie’s Supply Chain Intelligence Platform. Main ResponsibilitiesPerform data extraction, manipulation, cleaning, analysis and QA of large datasets Research energy industry data and suppliers to accurately and granularly classify spend into industry-specific schemas Evaluate categorized transactions to identify misclassified content, redundant and/or ineffective categorization logic Collaborate in a self-managed Agile team, an innovation Wood Mackenzie has adapted from the software development domain About You3+ years’ experience Bachelor’s degree required Proficient in Microsoft Office Suite with advanced Excel skills including vlookups, pivot tables and queries Exceptional analytical, organizational, problem solving, and time management skills with attention to detail Proven ability to learn quickly in a fast-paced environment, to manage multiple tasks and/or projects with changing priorities and to communicate effectively at all levels Ability to balance independent and team-based work Manages large volumes of data and ensures quality throughout the process Experience with data manipulation tools to solve complex quantitative problems, such as joining multiple different data sources or troubleshooting data discrepancies Creative and innovative problem-solving skills A self-starter who takes initiative, asks questions, and is eager to learn Proficiency in the English language required PlusesExperience in the energy industry Proficiency with databases Proficiency with Talend or other ETL software Experience in spend analysis Some programming experience with Python or Java preferred Prior experience analyzing external datasets using Python, SQL or visualization tools ExpectationsWe are a hybrid working company and the successful applicant will be expected to be physically present in the office at least 2 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. Equal OpportunitiesWe 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 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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