Data Science & Machine Learning Engineer (m / f / d) new

ON Consult GmbH; Düsseldorf; Hybrid; EUR 65.000 - 85.000; Vollzeit

Zusammenfassung

A leading IT consulting firm in Düsseldorf is seeking a Data Science & Machine Learning Engineer to design and deploy machine learning models for real-world applications. Candidates should have strong Python skills and over 3 years of experience in production environments. The role offers competitive compensation and collaboration with cross-functional teams. Remote work flexibility is available.

Leistungen

Competitive salary

Performance-based bonus

Advancement opportunities

Qualifikationen

• 3+ years of experience developing and deploying ML models in production environments.
• Strong communication skills to explain technical results to stakeholders.
• Familiarity with ethical AI principles.

Aufgaben

• Design and optimize ML models for forecasting and anomaly detection.
• Analyze structured and unstructured data for insights.
• Work with cloud platforms for model deployment.

Kenntnisse

Python

Machine Learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch)

SQL

Data preprocessing

Explainable AI

BI tools (e.g., Power BI)

Tools

AWS

Azure

Google Cloud Platform

Apache Airflow

Jobbeschreibung

Data Science & Machine Learning Engineer (m / f / d) About beON

beON is a leading IT consulting firm based in Germany, delivering state-of-the-art IT services and high-performance software solutions to enterprise clients. We specialize in end-to-end digital transformation, AI system design, IT security, and advanced hybrid cloud architectures. With headquarters in Kiel and Düsseldorf and offices in Munich, Berlin, Frankfurt, Hamburg, Vienna, Lisbon, and Hyderabad (India), we foster a modern, collaborative, and agile work culture.

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About the Role

As a Data Science & Machine Learning Engineer at beON , you will work on real-world industrial and enterprise use cases — from modeling sensor and process data to deploying AI models in live environments. Your role will contribute to building intelligent systems that optimize processes, improve quality, and drive efficiency. We welcome applicants from diverse data science backgrounds who are eager to apply their skills in impactful, production-ready solutions.

• Employment type : Permanent, Full-time
• Start : As soon as possible
• Language Requirements : English (German is a plus)
• Compensation : Competitive salary with performance-based bonus and advancement opportunities

Your Responsibilities

Design and optimize ML models for time series forecasting, anomaly detection, and computer vision (e.g., quality inspection)

Apply advanced techniques such as LSTM, CNN, XGBoost, PCA, clustering, and Explainable AI (e.g., SHAP, LIME)

Analyze structured and unstructured data from operational and sensor systems

Develop and maintain robust ML pipelines for training, validation, deployment, and monitoring

Collaborate with data engineers, solution architects, and IoT / Edge teams to ensure scalable integration

Use SQL and BI tools (e.g., Power BI) to prepare and visualize large datasets

Work with cloud platforms (e.g., AWS, Azure, GCP) for model deployment and MLOps lifecycle management

Your Profile :

3+ years of hands-on experience developing and deploying ML models in production environments

Strong Python skills and experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch)

Proficient in data preprocessing, feature engineering, and model validation techniques

Familiarity with Explainable AI (XAI), data governance, and ethical AI principles

Solid SQL skills and experience with BI / dashboard tools such as Power BI

Experience working with cloud-based ML services (e.g., SageMaker, Azure ML, Vertex AI)

Strong communication skills and ability to explain technical results to both technical and business stakeholders

Preffered Qualifications

Experience in Industry 4.0, manufacturing, or process automation projects

Familiarity with real-time / streaming data platforms, time series databases, and tools like Grafana

Understanding of MLOps pipelines and tools for automated model management and deployment

Experience with orchestration tools such as Apache Airflow or dbt

Application Process

Ready to take the next step in your career with beON? Send your CV [e-mail] with the subject line “Data Science & ML Engineer.” We respect your time — no cover letter required.

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