Senior Data Scientist, Price Forecasting

About Electricity MapsElectricity Maps is the world's most comprehensive electricity data platform - covering real-time, historical, and forecast data on electricity generation mix, power flows, carbon intensity, and prices.

Our work spans two distinct areas:

Sustainability: Clean, structured grid data for emissions reporting and carbon-aware decisions, used by companies like Google, Microsoft, Cisco, and Schneider Electric across 350+ zones with history back to 2015.

Power markets: Price and grid-fundamentals forecasts for traders, battery operators, and asset optimisers managing their exposure to energy markets.

What ties it together is the methodology: we standardise 100+ sources into one schema, flow-trace electricity across borders, and publish signals that reflect what a region actually consumed - not just what it generated. That physical picture of the grid is the foundation everything is built on.

About the role

We run short-term price forecasts at 15-minute granularity up to 72 hours ahead and there's always more signals to find and more accuracy to unlock. Price forecasting is the focus, and it draws on the same grid fundamentals data that underpins everything we build. You'll be hands-on in our models, exploring which signals are worth investigating, which features to build, and help evaluate what to look into and not.

Day to day that means working on day-ahead market modelling: evaluating new inputs, iterating on existing models, and shipping things that actually run in production amongst other things.

You'll be part of our Data team, collaborating closely across forecasting, modelling, and market expertise. Direction is set together, but you own the execution - from idea to production. We work closely with the commercial team, and through them you get direct feedback from prospects and customers - a loop that feeds back into model improvements and keeps us delivering value.

We move fast, stay pragmatic, and keep it lean so you can spend your time on the work that matters.

What You'll Do

• Build and improve short-term (72h) price forecasting models for the day-ahead market
• Evaluate and prioritise new signals - is this worth adding, how do we forecast it, how do we integrate it, what features do we derive from it?
• Debug and improve existing models when you spot gaps or degradation in production
• Collaborate across the Data team to shape what we investigate next
• Surface modelling insights that connect back to real product and customer decisions
• Own model performance end-to-end - from experimentation through to what's running live
• What You Won't DoWork from a fully scoped spec - we figure out what to build as much as how
• Focus purely on research without caring about whether it ships and works in production
• Operate in a siloed team disconnected from the product or the customer

What We're Looking For

• Must-haves
• Hands-on experience building price forecasting models for the day-ahead market
• Strong intuition for feature engineering and signal selection in time-series and market contexts
• Comfortable making calls on what to try, what to drop, and what to dig into - and owning those decisions
• Comfortable owning model performance in production, not just in development
• Understanding of how power market participants (traders, BESS optimisers, grid operators) actually use price forecast data
• Able to communicate model behaviour and limitations clearly to non-technical stakeholders
• Nice-to-haves
• Experience with probabilistic forecasting (prediction intervals, quantile regression)
• Familiarity with European power market mechanisms (EUPHEMIA, EPEX, Nord Pool)MLOps experience - model monitoring, retraining pipelines, drift detection
• Familiarity with ENTSO-E data and weather forecast data as forecasting inputs
• Our Stack
• Relevant to this role: GCP, Python, Pandas, Polars, Scikit-learn, MLFlow, BigQuery, Modal.
• You don't need to be an expert in all of these - we care more about how you think and learn than your exact tool history.
• Location: Copenhagen (in-office with flexibility)
• Type: Full-time
• Compensation: Competitive salary + stock options
• Benefits: 6 weeks vacation, health insurance, annual company offsite, lunch and snacks at the office