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# Short Term Forecasting Data Scientist

- **Company:** Eneco
- **Location:** Rotterdam, Netherlands
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Airflow, Automation of Tests, Microsoft Azure, Continuous Integration, Data Infrastructure, DevOps, Python (Programming Language), Machine Learning, Standard Sql, Software Engineering, SQL Databases, Data Streaming, Snowflake, Git, Performance Monitor, Machine Learning Operations, Databricks
- **Published:** September 7, 2026
- **Apply:** https://www.werkenbijeneco.nl/vacatures/short-term-forecasting-data-scientist-3194

## About the Role

You enjoy applying data science in a dynamic operational environment. You are interested not only in building models, but also in how they perform in practice and how people use their output to make decisions.
You communicate clearly with technical and non-technical colleagues. When priorities change or an incident occurs, you remain calm and focused. You take a pragmatic approach, investigate problems carefully, and follow through until there is a reliable solution.
You also bring:

 * A quantitative MSc degree;
 * At least 4 years of relevant experience in data science;
 * Strong Python and SQL skills;
 * An analytical and critical mindset, combined with a hands-on approach;
 * The ability to initiate improvements and work effectively with traders and other teams;
 * Attention to detail and a focus on robust, maintainable solutions;
 * Flexibility in an environment where priorities can change with market conditions and business opportunities.

Experience with energy markets, trading, software engineering, or machine learning engineering is an advantage, but not essential. Knowledge of DevOps, CI/CD, automated testing, MLOps, Git, Databricks, Airflow, Snowflake, or Azure Cloud is also welcome.
Do you recognise yourself in much of this profile, but not in every requirement? We still encourage you to apply. Your experience, perspective, and motivation may add something valuable to the team.

## Description

The energy transition creates a growing need for accurate and reliable forecasts. Wind and solar production change constantly, while customer demand and energy markets move throughout the day. Your work helps Eneco respond to these changes and contributes to a sustainable energy system that remains reliable and economically viable.
In this role, you see the impact of your work quickly. You do not develop models at a distance from the business. You work close to the trading operation, learn from real-time results, and use those insights to improve forecasts, tools, and processes. Your work helps reduce imbalance costs related to renewable energy production and customer demand.
You join a collaborative environment with short feedback loops, open communication, and room to experiment. You can propose ideas, take ownership, and develop your knowledge of energy markets, forecasting, and modern data platforms.

As a Short Term Forecasting Data Scientist, you combine hands-on operational work with the development of forecasting products.
You help ensure that traders can rely on accurate forecasts and clear information when making short-term trading decisions. This means monitoring forecast performance, analysing unexpected results, answering questions from traders, and taking action when models, systems, data flows, or forecasts do not behave as expected.
Incident handling is an important part of the role. When an issue occurs, you investigate what is happening, communicate clearly with the people involved, and help restore a reliable service. You stay calm, set priorities, and work with colleagues to find a robust solution.
At the same time, you work on longer-term improvements. You collaborate with the Forecast Product Development team to design, validate, operationalise, and improve forecasting products for wind and solar production and for power, gas, and heat consumption. Operational experience provides the context for these improvements: what you observe during daily operations helps you identify where models, monitoring, and processes can become better.
During your first months, the team supports you in building a strong understanding of the energy market, Eneco's role within it, and the relevant IT landscape. Operational work is not limited to this onboarding period. Everyone in the team continues to combine operational responsibilities with strategic development projects.

 * Monitoring forecast results and identifying irregularities, outliers, and performance issues;
 * Supporting day traders by answering questions about forecasts, positions, and monitoring results;
 * Investigating and resolving incidents involving models, systems, forecasts, or data flows;
 * Developing, improving, and validating forecasting models for renewable production and energy consumption;
 * Developing monitoring and reporting products that support Eneco's trading teams;
 * Working with the Forecast Product Development team to turn operational insights into structural improvements;
 * Contributing within a DevOps environment using technologies such as Databricks, Python, SQL, Azure DevOps, and CI/CD.

You enjoy applying data science in a dynamic operational environment. You are interested not only in building models, but also in how they perform in practice and how people use their output to make decisions.
You communicate clearly with technical and non-technical colleagues. When priorities change or an incident occurs, you remain calm and focused. You take a pragmatic approach, investigate problems carefully, and follow through until there is a reliable solution.
You also bring:

 * A quantitative MSc degree;
 * At least 4 years of relevant experience in data science;
 * Strong Python and SQL skills;
 * An analytical and critical mindset, combined with a hands-on approach;
 * The ability to initiate improvements and work effectively with traders and other teams;
 * Attention to detail and a focus on robust, maintainable solutions;
 * Flexibility in an environment where priorities can change with market conditions and business opportunities.

Experience with energy markets, trading, software engineering, or machine learning engineering is an advantage, but not essential. Knowledge of DevOps, CI/CD, automated testing, MLOps, Git, Databricks, Airflow, Snowflake, or Azure Cloud is also welcome.
Do you recognise yourself in much of this profile, but not in every requirement? We still encourage you to apply. Your experience, perspective, and motivation may add something valuable to the team.

You will join the Forecasting Analysis & Execution team within the Short-Term Desk at Eneco Energy Trade. The team develops continuously updated forecasts for energy demand and renewable energy production. These forecasts directly support short-term trading decisions.
The team values collaboration, open communication, and short feedback loops. Everyone combines operational responsibilities with long-term strategic development projects. This ensures that technical improvements remain closely connected to actual market decisions and day-to-day trading needs.
The environment is dynamic. Market developments and business opportunities can change priorities quickly. You work with colleagues who share knowledge, reflect on results, and improve products based on what they learn from the operation. There is room to experiment and propose ideas, but also a shared responsibility to keep forecasting products reliable when they are needed most.

Would you like to know more about this vacancy? Koen Bolijn, our Team Lead Forecast Analysts, will be happy to answer your questions via koen.bolijn@eneco.com.
For more information about the application process, please contact our Recruiter Kevin Wouters, Senior Recruiter Trade Community, via 06-40971932 or kevin.wouters@eneco.com.

 * Combine operational responsibility with long-term data science and forecasting projects
 * Develop and improve forecasting products that directly support short-term energy trading
 * Work closely with traders in a fast feedback environment, where you monitor performance, answer questions, and resolve incidents


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