Head of Data Console and Platform

  • Edinburgh, UK
  • Full-time
  • Verisk Business: Wood Mackenzie

Job Description

About Wood Mackenzie and Verisk

Verisk is a global analytics provider serving customers in insurance, energy, and finance.  Verisk has been serving clients for over 50 years by using proprietary data assets to deliver analytics and predictive modelling that help clients make better decisions. We offer solutions in rating, underwriting, claims, weather and catastrophe modelling, global risk management, energy and natural resources, and retail finance. 

Wood Mackenzie, the flagship company in Verisk’s Energy & Specialized Markets division, provides expert research and analysis in the energy domain to clients worldwide. Our oil, gas, power and renewables, chemicals, and metals and mining sector teams are located around the world to support our global client base, working with strategy and policy makers, business developers and market analysts, corporate finance, risk teams, and investors. Our analysts deliver research and consulting projects based on the assessment and valuation of thousands of individual assets, companies, and economic indicators, such as market supply, demand, and price trends.


About this Role

The Head of Data Console and Platform, reporting to the Chief Data Officer, is responsible for leading the development of our data platform.  Wood Mackenzie data engineers and research analysts will use the data platform to access our data, add or enhance it, and validate it for use in our expert research and analysis. This is a highly visible project and you will play a key part in shaping both the data platform and influence the growing data-centric culture at WoodMac. This is a rare opportunity to lead a transformative team within an established business.

If you are looking for the opportunity to lead a strategic project for a company looking to differentiate itself with its data quality and data management capabilities, then this is a great opportunity for you. 


Main Responsibilities

  • Act as the face of the Data Platform. Be a visible presence in the company as a champion for the new way of working and supporting buy-in to the new approach
  • Be a key member of the Data Organization Leadership Team, leading change that will transform our business
  • Build and lead a high-performance team dedicated to building a data management platform. 
  • Understand our desired data lifecycle and work with CDO to define key deliverables needed to create a platform supporting it. 
  • Learn our current processes and identify how they can be changed to become more efficient and better managed.  Be able to specify features and requirements for tools that deliver fit our data lifecycle while still enabling research analysts to insert their proprietary, value-added analytics into our data assets.
  • Understand technology to be able to review the implementation paths chosen by our development teams, insuring they are efficient and effective, and appropriate for our timelines, desired functionality, and real-life constraints.   
  • Understand how technologies can be integrated together to build and support our platform. 
  • Work with senior management and peers to form project plans, estimate timelines, size new work.
  • Work in an agile/scrum setting to write stories, lead development teams, evaluate progress to make sure we stay on-target to our goals. 
  • Make sure we use our resources efficiently and most productively.  Focus on completing our deliverables as efficiently as possible. 
  • Help train operational teams in using our tools across the company to support the ingestion, validation, and deployment of data assets in oil & gas, metals, mining, chemicals, and renewable energy.
  • Help teams transition their current data solutions, understanding complex Excel-based workflows and identifying short-term and long-term ways to automate those workflows, ultimately relying on the data platform we’re building. 
  • Understand and document dataflows; automate them to improve the quality of data they produce and the speed at which they improve it
  • Understand the value of data dictionaries and data models (physical and logical); able to review and understand the design of these
  • Create presentations, training, and other collateral as needed
  • Collaborate with other experienced leaders in the company to identify requirements, bottlenecks, and specific data needs
  • Develop processes and plans to improve and enhance data-management
  • Continually improve products; documenting a plan of product and feature improvement to move our platform towards an ideal state. 


Knowledge, Skills & Experience

  • Substantial relevant work experience.
  • Experience in the energy industry and/or willingness to upskill in this domain
  • First-hand experience with data-intensive systems
  • Strong understanding of data and data management
  • Experience working with data-centric products, and ideally also experience as a product manager or product owner. 
  • Experience managing projects where the key driver is data and/or the focus has been on delivering insights from data
  • Leadership skills, ideally with experience managing/leading a team
  • Experience designing or modifying systems that manage data.
  • Collaborative, comfortable working with executive, senior, as well as junior staff. 
  • An analytical mindset with an understanding of how to access and use data.
  • Able to plan ahead to ensure strong implementation management and execution
  • Attention to detail and high standards, pushing for the product to be well-received by users
  • Able to develop tools and processes that can be scaled to many employees that are geographically distributed but are all working on ingesting, organizing, and validating data.
  • Desire to drive change within the organisation, helping transform ways of working
  • Broad understanding of the tools and technologies for data management, sufficient for meaningful conversations with technical teams (architects and developers)
  • Familiarity with as much as possible of the following technology:
  1.           Data management tools, such as: SQL (any flavor), Pentaho, Alteryx
  2.           BI tools (Tableau, Spotfire, PowerBI)
  3.           Non-relational data stores such Neo4J, Mongo
  4.           General purpose and specialized programming languages (Python, R)
  5.           Cloud computing tech stack, in particular AWS but Azure and Google are also helpful


Additional Information

All your information will be kept confidential according to EEO guidelines.

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