Data Analyst - Exploration Team
Wood Mackenzie
GB-Edinburgh
10d ago

Company

For the past 40 years, Wood Mackenzie has established its reputation as a trusted source of intelligence, enriching lives by empowering clients with unique insight on the world’s natural resources.

Now, as part of the Verisk Analytics family, that legacy is even stronger. Aligning with the world’s leading data analytics company extends our ability to help clients overcome the toughest challenges with our unrivalled analysis and advice.

We will continue to build on the power of our existing approach to assess and value individual assets and companies, allowing our clients to pursue the most promising opportunities.

Together, we inspire and innovate the markets we serve providing invaluable intelligence that informs the strategic decisions that will ultimately shape the future direction of our global natural resources.

Function of Team

The Exploration team is responsible for the delivery of Wood Mackenzie’s Exploration Service. The Service provides a global view of exploration, including information on :

  • Which areas have seen the best exploration results over the last 10 years
  • Where is future exploration success expected to come from
  • Which oil and gas companies have been the most successful explorers
  • Where the key exploration wells are being, and will be, drilled
  • Role Purpose

    We are looking for a Data Analyst who collects, manages and enhances data to support Wood Mackenzie's rapidly evolving Exploration Service product suite.

    The successful candidate will assume responsibility for various tasks requiring data gathering, collation and formatting.

    They must have a technical understanding of data collection and management processes but also possess excellent interpersonal skills to maintain and improve relationships with the wider team, data providers and clients.

    As an integral member of an open, dynamic and innovative team, the Data Analyst will have a key role in helping identify and implement areas for improvement and growth within the team.

    They will be working alongside and supporting the existing DA with a view to fully taking over as the main DA.

    You would also be tasked with co-ordinating with other DAs in the Americas and APAC. Ensuring best practice, high standards and consistency.

    Main Responsibilities - Production and Delivery of Exploration Service

  • Working with a global dataset of exploration data (wells, fields, blocks etc) to provide input to analysis
  • Ensure application of data integrity checks to maintain data quality
  • Collect and compile industry data on a regular basis from various sources to maintain a regional upstream databases and team excel spreadsheets
  • Run extracts from the spreadsheets and databases for analytical tasks and check consistency and integrity of information held to maintain quality
  • To fulfil ad-hoc and scheduled requests for data on-time and with high quality, thus assisting the team with various research projects, such as report writing and consulting projects
  • Work closely with research analysts and data analysts in the team and across the region to identify areas where processes and products can be improved through innovation
  • Develop good working relationships with team members and wider Woodmac community
  • Working with visualisation tools (Spotfire) to identify data issues and trends
  • Look at further enhancements to the Spotfire tools, and / or other ways of presenting and publishing data
  • Must Have

  • The candidate will have experience working in a data-related role and be able to demonstrate an affinity with numbers and data handling
  • Accuracy of input and attention to detail are essential
  • Being able to manipulate large volumes of data and present this in a clear way
  • Ability to work as part of a team, whilst being able to prioritise own workload
  • Proficiency with MS Office suite including Access & Excel
  • Evidence where they have identified and implement process improvements in data structure, gathering, maintenance and delivery
  • Ability to innovate and drive to improve
  • Creativity and desire to think outside the box and improve our data delivery and collection
  • A deep understanding of what the data means and the value thereof
  • Desirable

  • Knowledge of Microsoft Enterprise Data Management Suite : SQL Server 2014, SQL Server Integration Services (SSIS) and SQL Server Analysis Services (SSAS)
  • Experience of leveraging web-scraping technology e.g. KAPOW
  • Basic understanding of data programming, such as VBA, SQL, Python, R
  • Experience with GIS systems
  • A knowledge of the exploration industry sector would be advantageous
  • Key Competencies

  • Issue identification, problem solving and analysis
  • Planning, implementation and control
  • Change orientation
  • Determined and resilient
  • Building and Maintaining Relationships
  • Collaboration
  • Wood Mackenzie Core Values

    Wood Mackenzie is a place where we are committed to supporting our people to grow and thrive. We value different perspectives and aspire to create an inclusive environment which encourages diversity and fosters a sense of belonging.

    Wood Mackenzie values each individual's contribution and helps them reach their full potential while sustaining an organisational culture of health and well-being.

    Our core values are :

  • Respect for the Individual
  • Persistence
  • Confidence with humility
  • Teamwork
  • We understand the importance of bringing your whole self to work and to achieving balance between work, family and other life commitments.

    We are open to considering flexible working arrangements to enable the greatest spectrum of talent to contribute to Wood Mackenzie's success.

    Apply
    Add to favorites
    Remove from favorites
    Apply
    My Email
    By clicking on "Continue", I give neuvoo consent to process my data and to send me email alerts, as detailed in neuvoo's Privacy Policy . I may withdraw my consent or unsubscribe at any time.
    Continue
    Application form