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Senior Machine Learning Engineer – Time Series & Forecasting at statworx · Katori

Asks for

The ad says“You have strong expertise in forecasting and practical experience in anomaly detection, predictive maintenance, or similar sensor-driven use cases”
The ad says“You have experience deploying machine learning systems into production and are familiar with software engineering and MLOps practices such as APIs, containers, CI/CD, testing, monitoring, and versioning”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”
The ad says“You have a solid understanding of practical forecasting topics such as multi-horizon forecasting, backtesting, probabilistic forecasting, and ideally hierarchical reconciliation”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”
The ad says“You have experience deploying machine learning systems into production and are familiar with software engineering and MLOps practices such as APIs, containers, CI/CD, testing, monitoring, and versioning”
The ad says“You have experience deploying machine learning systems into production and are familiar with software engineering and MLOps practices such as APIs, containers, CI/CD, testing, monitoring, and versioning”
The ad says“You have strong Python skills and hands-on experience with libraries and frameworks such as scikit-learn, PyTorch, darts, statsforecast, neuralforecast, or similar”
The ad says“You have at least five years of hands-on experience in machine learning or data science with a strong focus on time series and forecasting”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”
The ad says“You have at least five years of hands-on experience in machine learning or data science with a strong focus on time series and forecasting”
The ad says“You have a solid understanding of practical forecasting topics such as multi-horizon forecasting, backtesting, probabilistic forecasting, and ideally hierarchical reconciliation”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”
The ad says“You have at least five years of hands-on experience in machine learning or data science with a strong focus on time series and forecasting”
The ad says“You have experience deploying machine learning systems into production and are familiar with software engineering and MLOps practices such as APIs, containers, CI/CD, testing, monitoring, and versioning”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”
The ad says“You have experience deploying machine learning systems into production and are familiar with software engineering and MLOps practices such as APIs, containers, CI/CD, testing, monitoring, and versioning”
The ad says“You have a solid understanding of practical forecasting topics such as multi-horizon forecasting, backtesting, probabilistic forecasting, and ideally hierarchical reconciliation”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”
The ad says“You have strong Python skills and hands-on experience with libraries and frameworks such as scikit-learn, PyTorch, darts, statsforecast, neuralforecast, or similar”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”
The ad says“You have strong expertise in forecasting and practical experience in anomaly detection, predictive maintenance, or similar sensor-driven use cases”
The ad says“You have a solid understanding of practical forecasting topics such as multi-horizon forecasting, backtesting, probabilistic forecasting, and ideally hierarchical reconciliation”
The ad says“You have strong Python skills and hands-on experience with libraries and frameworks such as scikit-learn, PyTorch, darts, statsforecast, neuralforecast, or similar”
The ad says“You have strong Python skills and hands-on experience with libraries and frameworks such as scikit-learn, PyTorch, darts, statsforecast, neuralforecast, or similar”
The ad says“You have strong Python skills and hands-on experience with libraries and frameworks such as scikit-learn, PyTorch, darts, statsforecast, neuralforecast, or similar”
The ad says“You have strong Python skills and hands-on experience with libraries and frameworks such as scikit-learn, PyTorch, darts, statsforecast, neuralforecast, or similar”
The ad says“You have experience deploying machine learning systems into production and are familiar with software engineering and MLOps practices such as APIs, containers, CI/CD, testing, monitoring, and versioning”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”
The ad says“You have at least five years of hands-on experience in machine learning or data science with a strong focus on time series and forecasting”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”
The ad says“You have experience deploying machine learning systems into production and are familiar with software engineering and MLOps practices such as APIs, containers, CI/CD, testing, monitoring, and versioning”
The ad says“You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai”

About us

statworx is a leading Data & AI Consulting and Development company in the DACH region. For more than a decade, we have been helping organizations succeed with consulting, development, and training – delivering over 1,000 successful projects for more than 100 clients across nearly every industry.

From AI strategy to implementation, we develop innovative solutions. With expertise in AI Strategy, Generative AI, Agentic AI, Data & AI Engineering, and AI Infrastructure, we support organizations throughout their entire AI transformation journey.
Our goal: Creating value from Data & AI.

Our AI Development department serves as a facilitator for Data & AI transformation. We are taking a holistic approach, from the initial evaluation of AI maturity, through the design and development of data and AI solutions, to the practical implementation and scaling of AI solutions. Through our deep expertise in Data Engineering, Data Science, Machine Learning, we ensure that our clients gain the maximum value from their data.

Your tasks

Focus: Building and deploying production-ready machine learning solutions with a focus on time series forecasting, anomaly detection, and predictive maintenance on sensor and process data

You develop and deploy machine learning solutions for forecasting, anomaly detection, and predictive maintenance
You design robust end-to-end solutions from data preparation and feature engineering to model evaluation and production deployment
You select and implement the most suitable methods for each use case, ranging from strong statistical baselines to modern machine learning and deep learning approaches
You regularly collaborate with internal stakeholders and customer representatives to ensure close alignment and effective cooperation
You contribute to reliable ML engineering and MLOps setups across cloud, on-prem, and production environments and support the integration of models into industrial or production-related systems with constraints such as latency, security, and limited compute resources
You present solution concepts and handle technical communication with customer representatives during proposal and acquisition phases
You continuously follow developments in the field of time series and forecasting, including new methods, tools, and research, and apply this knowledge to deliver state-of-the-art solutions

Your profile

You have at least five years of hands-on experience in machine learning or data science with a strong focus on time series and forecasting
You have strong expertise in forecasting and practical experience in anomaly detection, predictive maintenance, or similar sensor-driven use cases
You have strong Python skills and hands-on experience with libraries and frameworks such as scikit-learn, PyTorch, darts, statsforecast, neuralforecast, or similar
You have experience applying statistical, feature-based, and modern neural forecasting approaches such as ARIMA or ETS, LightGBM or XGBoost, N-BEATSx or N-HiTS, TFT or PatchTST, as well as newer time series foundation models such as TimesFM, Chronos, TimeGPT, or Moirai
You have a solid understanding of practical forecasting topics such as multi-horizon forecasting, backtesting, probabilistic forecasting, and ideally hierarchical reconciliation
Experience with decision optimization such as pricing, replenishment, or resource allocation, or causal-informed decision support such as causal effect estimation, Double ML, or intervention-aware modeling is a strong plus
You have experience deploying machine learning systems into production and are familiar with software engineering and MLOps practices such as APIs, containers, CI/CD, testing, monitoring, and versioning
Initial experience with industrial or production-related deployments such as edge or on-prem setups, PLC, SCADA, or MES integration, or working under network, security, or latency constraints is a plus
You are a strong communicator with very good German skills at least at B2 level and excellent English skills at C1 level or higher
You enjoy occasional business trips to customer sites in Germany, Austria, and Switzerland

Our offer

Data & AI at the core: Work on diverse and challenging projects with leading clients across various industries – from data-driven solutions to innovative AI applications
Professional variety & growth: Tackle complex, multifaceted questions and continuously expand your expertise in your field as well as in the broader Data & AI landscape
Continuous development: We support your methodological, professional, and personal growth through regular feedback, tailored learning opportunities, training formats, and our mentoring program
Culture & collaboration: You’ll be part of an open, diverse, and respectful work environment with flat hierarchies, short decision-making paths, and a strong sense of team spirit
Modern ways of working: We embrace an iterative, modern work culture based on clear communication, ownership, and room for new ideas and creative freedom
Transparent compensation: We offer fair, structured, and transparent salary bands that are regularly reviewed and aligned with market and performance developments
Flexible work setup: Our modern Frankfurt office serves as your main workplace – while giving you the flexibility to work remotely on a regular basis and up to four weeks per year from within the EU
Mobility & well-being: Benefit from a subsidized Germany Ticket and discounted access to sports and wellness offerings through Wellpass
Equipment & extras: High-quality IT equipment (e.g., MacBook Pro), regular team events, childcare support, and attractive employee discounts complete your package

Your application

Simply apply via the application form and attach your current CV including a description of your methodological skills. We will contact you as soon as possible. If you have any questions on your application, you can reach us at jobs@statworx.com.

What is particularly important to us is that we value the uniqueness of each person and always treat each other as equals. Different backgrounds, attitudes and ideas enrich us and form the basis of our success. That's why we welcome every application - regardless of gender, nationality, ethnic and social origin, religion, ideology, disability, age, or sexual orientation and identity.