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About the Role

We are seeking a data scientist to build data pipelines, integrate internal and external data, and generate market-leading insights using classical and ML techniques. The role focuses on demand, renewables, and transmission system fundamentals forecasts, initially for the GB intraday power market, to support Octopus Energy Trading's mission of reshaping the future of energy and accelerating the transition to a Net Zero world.

Responsibilities

• Explore data types for effective GB intraday power market trading.
• Build, improve, and maintain models for electricity demand and renewable generation forecasts in GB and Western Europe.
• Identify high-quality, novel data sources for forecasts.
• Develop forecasting frameworks and tools.
• Maintain and automate forecasting processes with checks and alerting.
• Utilize forecasting models to build or enhance price forecasts.
• Collaborate with Trading, Renewables, Flexibility, and other teams to leverage combined knowledge and data.

Requirements

• Experience with Python is essential.
• Good understanding of forecasting techniques and ability to build a simple baseline and iterate quickly.
• Ability to communicate approach, including strengths and limitations.
• Ability to quickly understand commercial and industry concepts.
• Team player excited about ownership across projects and tools.
• Passion for driving towards Net Zero.
• Experience with Machine Learning is essential.
• Experience in the electricity industry in GB is useful but not required.

Skills

• Python
• Forecasting techniques
• Machine Learning

Location

• GB

Work Type

• Full-time

Experience Level

• Mid-level

About the Company

• Octopus Energy Trading is part of Octopus Energy Group, focused on creating an innovative approach to trading to accelerate the transition to a Net Zero world.
• The company is building cutting-edge technology to optimize energy flexibility from domestic EV charging to grid-scale batteries.
• Octopus has a tech-first approach with all trading and analytics tools built in-house.