Data Scientist

• As a Data Scientist, you’ll play a key role in keeping Tibber’s energy trading function one step ahead. You’ll build and continuously improve a whole portfolio of models: the forecasts our traders lean on when they buy power, and the models that decide how our virtual power plant puts thousands of home batteries and electric cars to work. You will have a direct, measurable impact on our trading outcomes
• Build and improve day-ahead energy consumption forecasting models that the trading team uses to make power purchase decisions
• Own the full model lifecycle - problem framing, data sourcing, model development, production deployment, and ongoing performance monitoring
• Take models from exploratory notebooks to reliable, production-ready Python systems built for live trading conditions
• Collaborate with backend engineers to bridge model outputs into production infrastructure
• Diagnose and respond to operational issues - missing data inputs, model drift, or unexpected forecast failures, without waiting to be asked
• Continuously raise the accuracy and reliability of our established forecasting systems with direct impact on trading outcomes

Benefits

• Flexible work hours
• Offices in Stockholm, Helsinki, Berlin and Førde
• “No shoe” policy at the office to enhance the feeling of coming home - a great opportunity when it comes to showing off your slipper fashion range
• Annual pop-up office, to gather the work force to work, explore a new city and spend time together- We see it as a plus bust not a must if you also bring: experience in energy, power markets, or demand forecasting in regulated markets
• Enjoys owning a project end-to-end - from scoping and data sourcing to a measured outcome
• Are excited by AI tools - and how they are changing the way data scientists work and actively look for ways to build smarter, faster workflows with them
• You are driven by impact and know how to turn strategy into execution. You’re used to fast-paced environments and thrive when given clear goals and high accountability. We believe you’ll thrive here if you:
• Have built and deployed forecasting or time-series models in production - not just in notebooks, and can speak to how those models held up in practice
• Are a team player - you learn from those around you and share what you know freely
• Are curious about the energy trading domain - and motivated to understand the market mechanics behind the models, not just the math
• Write clean, maintainable Python - this is your primary language and you use it comfortably across the full stack from data wrangling to production code- We usually respond within two weeks
• Contact: Linnea Strand