Senior Data Scientist – Python, ML & Signal-Processing

About the Position

Senior Data Scientist – Python, ML & Signal-Processing

DATATRONiQ is a Deep-Tech startup from Germany specializing in Industrial IoT and Edge AI. As a Senior Data Scientist with us, you will train machine learning models based on real machine and sensor data – worldwide, from medium-sized manufacturers to DAX corporations. Anomaly detection, predictive maintenance, and real-time quality monitoring. The data is real, the machines are in ongoing production, and your models will help determine whether a plant runs as planned or stands still unexpectedly. If you prefer seeing models in productive use rather than optimizing them in notebooks, then please get in touch with us.

Location: Stuttgart, Ulm, or Berlin

Experience: Senior · 3+ years of experience

Stack: Python · PyTorch · scikit-learn · ONNX · GPU

All positions: Apply to [email protected]

Your contact person:

Andrea Walter

Human Resources

Email: [email protected]

About the Role

You will be responsible for the entire data science lifecycle – from exploration through feature engineering and model training to deployment and validation, depending on the customer situation on Edge-Gateway, on-prem server, or in the cloud. The time series come from real industrial controls via OPC-UA and MQTT; feature engineering here means signal processing on noisy sensor data, not shuffling pre-prepared table columns. Your models will be quantized, exported to ONNX, and run directly where production needs them – with all the consequences that has for model choice, latency, and memory usage.

Your stack: Python, PyTorch or scikit-learn, ONNX for edge deployment, and the common MLOps tools for versioning and reproducibility.

We work in a small, closely coordinated team. Code reviews and pair programming are part of our daily routine. On Fridays, we show interesting findings from the web and new tools in our Show-and-Tell sessions. As a Data Scientist, you will work closely with Data Engineers and Backend Developers: you build the models, they build the pipelines, and together we bring both into production.

Your Responsibilities

• You will train ML models for anomaly detection, predictive maintenance, and quality monitoring and validate them on real production data and time series from industrial controls.
• You will perform feature engineering on noisy sensor and machine signals (OPC-UA, MQTT, MES exports), including signal processing and filtering.
• You will deploy models to where the customer needs them – Edge-Gateway, on-prem server, or cloud: quantization, ONNX export, sometimes with limited CPU and RAM resources, tuning, and monitoring in the field.
• You will work closely with Data Engineers and Backend Developers to ensure models run reliably in our production pipelines – not as prototypes in notebooks.
• You will measure models not just by their F1 or AUC scores, but by what they really achieve in production: fewer unplanned downtimes, higher output, fewer errors.
• You will actively contribute to the product roadmap and technical decisions – we expect opinions, not just ticket completion.

What You Should Bring

• Completed degree in Data Science, Computer Science, Mathematics, Physics, or a related field.
• At least three years of very hands-on experience with Python, common ML frameworks (PyTorch, scikit-learn, etc.), and model deployment in production environments.
• Experience with time series analysis and signal processing – we do not expect PhD-level knowledge, but you know why a naive MLP fails on noisy industrial signals.
• Basic knowledge of MLOps: versioning of models and data, reproducible pipelines, tests for ML code.
• Very good English skills in speech and writing.
• You can justify technical decisions and represent them in the team – even against a majority if you have strong arguments.
• Bonus: Experience with edge deployment (ONNX, TensorRT, quantization), industrial protocols (OPC-UA, MQTT), or LLMs for chat and agentic tasks.

What Awaits You

• Real end-to-end responsibility: from the conception of data collection in production through the pipeline to model inference – on Edge-Gateway, on-prem server, or in the cloud.
• The team decides architecture, tooling, and model strategy itself.
• Agentic tools in everyday use: Codex, Claude Code, and new development practices – we try out and use what works early on.
• Mostly on-site in Stuttgart, Ulm, or Berlin – Industrial IoT projects for customers worldwide, from medium-sized manufacturers to DAX corporations, on real production data.

Next Steps

Have we piqued your interest?

At DATATRONiQ, you are not just a small cog in the machine; you shape and contribute your ideas. You will have the unique opportunity to work on a product that has the potential to significantly impact the industrial manufacturing sector. If you want to use your skills to solve challenging problems and actively contribute to our team, we would love to speak with you!

Contact us at [email protected]. We look forward to your application!

We ask recruitment agencies and headhunters to refrain from contacting us.

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