over 1 year ago
Frankfurt, GermanySenior
Responsibilities
- Develop and implement machine-learning solutions for time-series forecasting, anomaly detection, and predictive maintenance.
- Design robust end-to-end solutions from data preparation and feature generation through model evaluation and production deployment.
- Select and implement appropriate statistical, machine-learning, and deep-learning methods for each use case.
- Collaborate closely with internal stakeholders and customer representatives.
- Support stable ML engineering and MLOps setups across cloud, on-premises, and production environments.
- Integrate models into industrial or production-related systems while considering latency, security, and resource constraints.
- Present technical solution concepts and provide technical communication during proposal and acquisition processes.
- Track developments in time-series forecasting and apply relevant knowledge to customer projects.
Requirements
- At least five years of practical experience in Machine Learning or Data Science with a clear focus on time series and forecasting.
- Strong forecasting expertise and practical experience with anomaly detection, predictive maintenance, or comparable sensor-based use cases.
- Very good Python skills and practical experience with tools such as scikit-learn, PyTorch, darts, statsforecast, and neuralforecast.
- Experience with ARIMA, ETS, LightGBM, XGBoost, N-BEATSx, N-HiTS, TFT, PatchTST, TimesFM, Chronos, TimeGPT, or Moirai.
- Understanding of multi-horizon forecasting, backtesting, probabilistic forecasting, and ideally hierarchical reconciliation.
- Experience with production machine-learning systems and software-engineering and MLOps practices including APIs, containers, CI/CD, testing, monitoring, and versioning.
- Industrial or production-related deployment experience, such as Edge or on-premises environments, PLC, SCADA, or MES integration, is advantageous.
- Experience with decision optimization, causal analysis, Double ML, or intervention-aware modeling is a plus.
- Very good German skills at least at B2 level and excellent English skills at C1 level or higher.
- Willingness to make occasional business trips to customer sites in Germany, Austria, and Switzerland.
Benefits
- Work on varied Data and AI projects for notable customers across multiple industries.
- Professional development through regular feedback, individual support, training opportunities, and a mentoring program.
- Open, diverse, respectful culture with flat hierarchies, short decision paths, and strong teamwork.
- Modern iterative working environment with autonomy and opportunities to contribute ideas.
- Frankfurt office as the central workplace with regular remote-work options and up to four weeks per year working from another EU country.
- Discounted Deutschlandticket and reduced-price access to sports and wellness services through Wellpass.
- High-quality IT equipment such as a MacBook Pro, team events, childcare subsidies, and employee discounts.
- Structured and transparent salary levels adjusted regularly to market and performance developments.