Company: EURES
Country: Netherlands
Type: Onsite
Employment: Contract
Description: Data Scientist Start date 01-12-2026 Hours p/w 40 End date 01-06-2027 Hourly rate € 8500 Location Rotterdam Deadline 13-10-2026 Field Energy Service Freelance About the assignment You implement the OpenSTEF forecasting framework for all LV transformer points (23,000) and contribute to improving short-term grid load forecasts (short horizon <7 days). The focus is on production suitability, explainability and reusability of improvements and models. What will you do - Analysis of current forecast quality and selection of locations, horizons and situations with the greatest potential for improvement. - Backtesting and benchmarking OpenSTEF methods against the existing reference, with appropriate quality metrics and segmentation. - Develop solutions for difficult patterns: flatlines, peaks, missing values, unpredictable assets and limited historical data. - Experiments with model selection, ensembles, calibration and confidence intervals. - Exploration and validation of foundation model capabilities as soon as they are applicable and can be used responsibly. - Translation of successful experiments into maintainable Python code, tests, configuration and reproducible pipelines. - Improvement of monitoring of forecast quality, data quality and model behavior. - Contribute to OpenSTEF (issues, documentation, reviews, pull requests) when improvements are also valuable to the community. - Transfer of knowledge to the team and clear documentation of choices, results and next steps. Desired profile - Education: Completed university education in data science, econometrics, mathematics, statistics, electrical engineering, computer science or similar. - Experience: Demonstrable experience with time-series forecasting and machine learning in a professional environment. - Programming skills: Very good command of Python, including testing, code reviews and version control. - Methods and tooling: Experience...
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