Team Lead Data Science

Lead the Energy Data Science team, a focused team of three data scientists building and operating the forecasting systems at the heart of Enpal's energy trading operation. This is a hands-on leadership role (~65% technical, ~35% leadership) where you will own short-term and long-term models, risk simulations, and drive outcomes that directly inform trading decisions across one of Europe's largest residential energy communities.

What you'll do

• Research, develop, and productionize time series forecasting models for energy markets (e.g. load and generation forecasts), owning the full lifecycle from data exploration and feature engineering through model training, evaluation, deployment, monitoring, and retraining.
• Contribute to MLOps infrastructure: experiment tracking, model versioning, automated retraining pipelines, and production observability.
• Communicate forecasting model decisions and performance to C-level leadership, and stakeholders in trading and risk management functions, connecting business understanding and impact with deep technical knowledge.
• Collaborate closely with Traders/ Portfolio Managers, Data Engineers, Software Engineers, and Product to deliver well-engineered, reliable data science products.
• Own and evolve the team's forecasting roadmap, including future use cases such as long-term forecasting (1–2 year horizon), price forecasting, and probabilistic risk simulations.
• Lead, mentor, and develop a team of data scientists — including 1:1s, performance reviews, career development, and hiring decisions.
• Foster a culture of continuous learning, engineering quality, and technical growth.

What you'll need

• University degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field.
• 5+ years of industry experience in machine learning, with a strong focus on time series forecasting or data science in the energy sector.
• 2+ years of experience leading a data science team or multi-person project, including formal people management responsibilities (performance reviews, mentoring, hiring).
• Proficiency in Python and SQL, with strong software engineering fundamentals: testing, code quality, version control, and CI/CD.
• Proven experience deploying, monitoring, and maintaining machine learning models in production environments.
• Hands-on experience with MLOps practices and tooling: experiment tracking, model registries, automated retraining workflows, and CI/CD for ML.
• End-to-end ownership mindset: proven ability to drive projects from research through production, and to deliver outcomes through a team.
• Fluent in English.

Nice to have

• Experience with long-term forecasting (seasonal, multi-year horizons) or scenario modelling.
• Experience with probabilistic forecasting or uncertainty quantification (e.g. conformal prediction, quantile regression, Monte Carlo simulation).
• Experience with price forecasting or price forward curves in energy markets.

What they offer

• Work at Germany's first green unicorn with a highly motivated, diverse team.
• Hybrid working concept with Workflex option to relocate abroad for up to 30 days a year.
• Modern office in Berlin-Friedrichshain with height-adjustable desks, table tennis, and barista coffee.
• 29 + 2 vacation days, discounted Wellhub membership, and corporate benefits.