Short Term Forecasting Data Scientist

What are you going to do?

We’re looking for a full‑stack quant/data scientist who can turn ideas into production-ready forecasting products fast. In this role, you’ll own the entire lifecycle: from concept to live deployment. Your mission is to reduce latency, enhance forecast quality, and deliver trader-ready signals that directly impact P&L. You’ll work hands-on with Python, Spark/Databricks, MLflow, CI/CD, monitoring, and APIs, always balancing time-to-market with fit-for-purpose accuracy.

You’ll also help us uncover how weather patterns and diverse data sources influence our energy portfolio. This role goes beyond accuracy and speed; it’s driving commercial impact: improving P&L, reducing imbalance risk, and building forecasting products that give our traders a competitive edge. Working alongside analysts, meteorologists, traders, engineers and data scientists, you’ll create tools that sit at the heart of our trading strategy.

You're responsible for

• Own end-to-end forecasting products: from problem framing and data strategy to modeling, back testing, deployment, monitoring, and continuous improvement;
• Ship quickly: prioritize time-to-market, deliver “good-enough” baselines fast, and iterate toward P&L impact (balancing speed vs. accuracy);
• Productionize at scale: build forecasting products that can adapt to changing portfolios, with robust MLOps practices (e.g., model versioning, automated deployment, monitoring);
• Risk & impact focus: Proactively reduce imbalance costs and risk and collaborate with analysts to set up the right KPIs to measure value. Also proactively be aware of low hanging fruit to improve;
• Developing and improving short-term forecast products tailored to the needs of our trading desks;
• Acting as a sparring partner for operations, engineering and maintaining strong communication across departments;
• Contributing to a forward-looking strategy and exploring new forecasting methodologies and contributing to the long-term forecasting roadmap.

What do we ask?

• Experience: At least 3+ years in a forecasting or data science role, ideally in energy markets, trading, or other time-sensitive domains;
• Technical: Strong in Python and core data science libraries (pandas, NumPy, scikit-learn); proven ability to scale solutions with Spark/Databricks;
• Forecasting expertise: Hands-on experience with time-series modeling and short-term optimization; probabilistic methods and back testing discipline are a plus;
• Domain knowledge: Background in meteorology or weather-driven forecasting is highly valued, especially experience with NWP models and ensemble blending;
• Engineering mindset: Comfortable sparring with engineers on query optimization, job scheduling (Airflow or Databricks Workflows), and CI/CD best practices. You understand how to design solutions that are reliable, maintainable, and production ready;
• Entrepreneurial approach: You thrive in dynamic environments, take initiative, and look for gaps to maximize revenues;
• Collaboration & communication: Skilled at bridging technical and commercial teams; able to turn complex insights into actionable decisions.

What do we offer?

• Gross annual salary between €86 and €120: including FlexBudget, 8% holiday allowance, and, depending on your position, a bonus or collective profit sharing.
• FlexBudget: cash it out, use it to buy extra vacation days, or save it for something fun—the choice is yours.
• Plenty of opportunities for personal development: Eneco is fully committed to personal and professional development.
• Hybrid working: home, office, or abroad. You work 40% in the office, 40% from home, and 20% flexibly. With your manager's permission, you may work abroad for a maximum of 3 weeks per year (within approved countries), up to a maximum of 2 consecutive weeks.