Senior Data Analyst - Lens Hydrogen
Apply remote type Hybrid locations Edinburgh, GB time type Full time posted on Posted Yesterday job requisition id JR1434 Wood Mackenzie is the global data and analytics business for the renewables, energy, and natural resources industries. Enhanced by technology and enriched by human intelligence, 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, enables customers’ decisions through real-time analytics, consultancy, events, and thought leadership. WoodMac.com Wood Mackenzie Brand Video Wood Mackenzie Values Inclusive – 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 Role Purpose As part of the Data team working on the delivery of data for Lens Hydrogen, the Senior Data Analyst will develop costs, emissions, and other data models for the low-carbon hydrogen and derivatives market. Leveraging Wood Mackenzie’s proprietary data, models, and expertise, these models will enable the assessment of evolving trends in the hydrogen market. There will be close collaboration with cross-functional teams including research, product, engineering, and design to build and develop new models and generate new datasets for Lens Hydrogen. Main Responsibilities Develop code for data pipelines behind costs, emissions, and other models Develop data quality rules and embed them into packages Create data visualisations for data checks with BI tools Work with Research to define and implement the latest model methodologies in code Collaborate with Engineering teams to implement and test models Maintain and debug code in existing models and understand cases where model logic does not hold Review existing coverage of datasets generated by models and recommend ways to expand data coverage Conduct regular dataset quality profiling to identify areas to improve data quality Conduct regular code reviews to ensure code efficiency and identify ways to scale model development Document methodologies implemented in models for further analysis Document code clearly to ensure readability and maintainability Apply problem-solving and data analysis skills to identify and implement solutions for data pipeline inefficiencies Knowledge and Experience At least 3 years of experience in data ETL – extracting, transforming, and loading data Strong proficiency in Python and SQL Ability to write efficient and high-quality code for production Experience with SQL databases for data management Experience in implementing data quality rules Demonstrated ability to visualize data through BI tools Experience in implementing models to generate data is a plus A passion for working with challenging data, including large datasets and real-time data A curiosity about the energy transition and developments in the hydrogen market Key Competencies Issue identification and problem-solving Attention to detail Planning and implementation Efficiency-focused Determined and resilient Continuous improvement Creativity Building and maintaining relationships Communication Personal impact Collaboration Equal Opportunities We are an equal opportunities employer, committed to recruiting the best people regardless of their race, colour, religion, age, sex, national origin, disability, or protected veteran status. If 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. Why work here?
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us! About Us
Our Work Experience is the combination of everything that's unique about us: our culture, our core values, our commitment to sustainability, and our recognition programs, but most importantly, it's our people. Our employees are self-disciplined, hardworking, curious, trustworthy, humble, and truthful. They make choices according to what is best for the team and live for opportunities to collaborate and make a difference.
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Apply remote type Hybrid locations Edinburgh, GB time type Full time posted on Posted Yesterday job requisition id JR1434 Wood Mackenzie is the global data and analytics business for the renewables, energy, and natural resources industries. Enhanced by technology and enriched by human intelligence, 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, enables customers’ decisions through real-time analytics, consultancy, events, and thought leadership. WoodMac.com Wood Mackenzie Brand Video Wood Mackenzie Values Inclusive – 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 Role Purpose As part of the Data team working on the delivery of data for Lens Hydrogen, the Senior Data Analyst will develop costs, emissions, and other data models for the low-carbon hydrogen and derivatives market. Leveraging Wood Mackenzie’s proprietary data, models, and expertise, these models will enable the assessment of evolving trends in the hydrogen market. There will be close collaboration with cross-functional teams including research, product, engineering, and design to build and develop new models and generate new datasets for Lens Hydrogen. Main Responsibilities Develop code for data pipelines behind costs, emissions, and other models Develop data quality rules and embed them into packages Create data visualisations for data checks with BI tools Work with Research to define and implement the latest model methodologies in code Collaborate with Engineering teams to implement and test models Maintain and debug code in existing models and understand cases where model logic does not hold Review existing coverage of datasets generated by models and recommend ways to expand data coverage Conduct regular dataset quality profiling to identify areas to improve data quality Conduct regular code reviews to ensure code efficiency and identify ways to scale model development Document methodologies implemented in models for further analysis Document code clearly to ensure readability and maintainability Apply problem-solving and data analysis skills to identify and implement solutions for data pipeline inefficiencies Knowledge and Experience At least 3 years of experience in data ETL – extracting, transforming, and loading data Strong proficiency in Python and SQL Ability to write efficient and high-quality code for production Experience with SQL databases for data management Experience in implementing data quality rules Demonstrated ability to visualize data through BI tools Experience in implementing models to generate data is a plus A passion for working with challenging data, including large datasets and real-time data A curiosity about the energy transition and developments in the hydrogen market Key Competencies Issue identification and problem-solving Attention to detail Planning and implementation Efficiency-focused Determined and resilient Continuous improvement Creativity Building and maintaining relationships Communication Personal impact Collaboration Equal Opportunities We are an equal opportunities employer, committed to recruiting the best people regardless of their race, colour, religion, age, sex, national origin, disability, or protected veteran status. If 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. Why work here?
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us! About Us
Our Work Experience is the combination of everything that's unique about us: our culture, our core values, our commitment to sustainability, and our recognition programs, but most importantly, it's our people. Our employees are self-disciplined, hardworking, curious, trustworthy, humble, and truthful. They make choices according to what is best for the team and live for opportunities to collaborate and make a difference.
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