Global Gas Analytics Lead: Build Function & Own Insights

Global Gas Analytics Lead: Build Function & Own Insights

Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
Modo Energy

At a Glance

  • Tasks: Design and own the gas analytics function, developing models and insights from scratch.
  • Company: Modo Energy, a cutting-edge data platform driving the energy transition.
  • Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
  • Other info: Join a dynamic team focused on innovation and sustainability.
  • Why this job: Make a real impact in the energy sector while engaging directly with clients.
  • Qualifications: Strong analytical skills and experience in data modelling and research.

The predicted salary is between 63000 - 77000 £ per year.

Modo Energy, a globally scaling data platform for the energy transition, seeks a Global Gas Analyst in London to design and own the gas analytics function from scratch.

You’ll develop models, data, forecasts, and research to show clients how gas moves and impacts portfolios.

You’ll publish insights, engage with clients directly, and contribute to the Global Analytics group, reporting to the Director of European Product.

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Global Gas Analytics Lead: Build Function & Own Insights employer: Modo Energy

Modo Energy is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those passionate about the energy sector and SaaS solutions. With competitive compensation, equity options, and a hybrid work model, employees are empowered to thrive while enjoying a healthy work-life balance. The company prioritises professional growth, offering ample opportunities for development and collaboration within a supportive team environment in the vibrant Greater London area.

Modo Energy

Contact Details:

Modo Energy Recruitment Team

We think you need these skills to ace Global Gas Analytics Lead: Build Function & Own Insights

Communication Skills
Problem-Solving Skills
SQL
Python
Automation
Attention to Detail
Data Engineering