Energy Forecasting & Optimization Engineer (m/f/d)
On-siteKarlsruhe, Baden-Wurttemberg, Germany
Job Summary
Develop and improve time-series forecasting models for industrial electricity consumption, PV generation, and other energy-relevant signals. Extend forecast services with probabilistic outputs and build optimization models for industrial energy flexibility, production decisions, and storage systems. Evaluate model quality on noisy, incomplete data and design workflows integrating forecasts, uncertainty measures, and physical constraints into downstream optimization. Construct simulation, replay, and benchmarking frameworks to validate model behavior before live deployment. Support technical interpretation of model behavior in real customer environments while implementing robustness through plausibility checks and fallback mechanisms. This role combines deterministic and probabilistic forecasting with mathematical optimization to drive the energy transition in industry.
Required Qualifications
- strong applied experience in time-series and probabilistic forecasting
- forecast calibration, uncertainty evaluation, backtesting, and model validation
- strong understanding of mathematical optimization, especially LP/MILP
- ability to model real-world systems through objectives, constraints, and operational rules
- experience combining forecasts, uncertainty, optimization, and LLM-based orchestration of time-series pipelines
- experience working with noisy and incomplete real-world data
- ability to turn models into reliable production services
Desired Qualifications
- industrial energy systems, electricity markets, PV, BESS, or flexible loads
- simulation, replay testing, or benchmarking frameworks
- industrial hardware and control systems
- basic thermodynamics
- model deployment, monitoring, or explainability
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