Note: The job is a remote job and is open to candidates in USA. Modo Energy is focused on providing innovative solutions in the energy sector, and they are seeking an Energy Statistician to develop mathematical and statistical models for data analysis. The role involves building tools for battery energy storage systems, analyzing complex datasets, and collaborating with product teams to ensure alignment with user needs.
Responsibilities
- Develop mathematical or statistical models to analyze and interpret data
- Build novel and industry-leading models and analyses
- Produce tools used by organizations across the energy transition to finance, build, benchmark, and operate battery energy storage systems
- Using statistical techniques, source, process, analyze, and interpret large and complex datasets within our growing forecast offering
- Develop our power market and dispatch models to grow and enhance Modo's product offering, using Python and optimization toolsets
- Apply statistical methods to solve practical problems in the business, determining what data are needed to answer specific questions or problems
- Work closely with our product function to ensure the product we deliver aligns closely with user needs and provides value to the wider Modo team
- Stay up to date with the latest market regulations and their impact on the broader energy landscape
- Use statistical software to analyze data and create visualizations to aid decision making in business
- Interpret data and communicate analyses to technical and nontechnical audiences
Skills
- Master's degree in Engineering, Computer Science, Mathematics, or a related quantitative field plus one year of full-time experience in occupations involving data analysis, statistical analysis, engineering, energy consulting or related occupations
- Develop mathematical or statistical models to analyze and interpret data
- Build novel and industry-leading models and analyses
- Produce tools used by organizations across the energy transition to finance, build, benchmark, and operate battery energy storage systems
- Using statistical techniques, source, process, analyze, and interpret large and complex datasets within our growing forecast offering
- Develop our power market and dispatch models to grow and enhance Modo's product offering, using Python and optimization toolsets
- Apply statistical methods to solve practical problems in the business, determining what data are needed to answer specific questions or problems
- Work closely with our product function to ensure the product we deliver aligns closely with user needs and provides value to the wider Modo team
- Stay up to date with the latest market regulations and their impact on the broader energy landscape
- Use statistical software to analyze data and create visualizations to aid decision making in business
- Interpret data and communicate analyses to technical and nontechnical audiences
- Use of Python and R for data analysis
- Use of the scientific computing stack for data analysis, data science, and machine learning: Numpy, Pandas, SciPy, and ScikitLearn
- Use of optimization methodologies and linear programming, including building and refining mathematical models for decision-making in the energy sector
- Development of production-cost models and capacity expansion models for energy market projections, and cost-benefit analyses for energy projects using modeling software: PLEXOS, Uplan, or ProMod
- Financial modeling and analysis for energy projects
- Preparation of technical reports and presentations using data visualization tools including Power BI and Excel
Company Overview
Modo Energy is an energy asset analysis platform that provides users with data, research, and benchmarking tools for energy storage. It was founded in 2019, and is headquartered in London, England, GBR, with a workforce of 51-200 employees. Its website is https://modo.energy/.Company H1B Sponsorship
Modo Energy has a track record of offering H1B sponsorships, with 2 in 2025, 1 in 2024. Please note that this does not guarantee sponsorship for this specific role.
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