Data Scientist (f/m/div.)

• MSc or PhD in Data Science, Artificial Intelligence, Machine Learning, Computer Science, Mathematics, Statistics, Engineering, Physics or a related field.
• Academic or professional background in machine learning, statistics, optimization or data-driven problem solving.

• Experience developing Machine Learning, Artificial Intelligence or Advanced Analytics solutions.
• Hands-on experience working with complex datasets in industrial, engineering, manufacturing or technical environments.
• Experience contributing to end-to-end data science projects, including data preparation, model development, validation and deployment.
• Exposure to manufacturing, process development, industrialization, quality improvement or equipment-related analytics is considered an advantage.

Know-how

1. Machine Learning & Advanced Analytics

• Knowledge of machine learning methods, including regression, classification, clustering, anomaly detection, forecasting and optimization.
• Experience applying techniques such as feature engineering, model evaluation, hyperparameter tuning and model explainability.
• Familiarity with deep learning approaches is a plus.

2. Statistics & Experimental Methods

• Knowledge of statistical analysis, probability and experimental data analysis.
• Experience with hypothesis testing, regression analysis, statistical significance and data interpretation.
• Understanding of process variability, capability analysis, performance indicators and Design of Experiments (DoE).

3. Programming & Data Science Tools

• Proficiency in Python and good knowledge of SQL.
• Experience with data science and machine learning libraries such as Pandas, NumPy, Scikit-learn, SciPy, Matplotlib, Seaborn, Plotly, PyTorch or TensorFlow.
• Familiarity with Git and collaborative software development practices.

4. MLOps & Industrial Deployment

• Understanding of MLOps concepts, including model versioning, testing, reproducibility, CI/CD and monitoring.
• Experience with cloud-based AI platforms, preferably Databricks, is an advantage.
• Knowledge of APIs, containers and deployment concepts is beneficial.

5. Industrial Data & Manufacturing Systems

• Experience working with structured, semi-structured and time-series data.
• Familiarity with manufacturing systems and data sources such as MES, PLC, SCADA, Historian systems, test systems or production databases.
• Understanding of manufacturing KPIs such as OEE, yield, scrap, downtime, cycle time, rework and process capability is an advantage.

Languages

• Fluent English, written and spoken.

Working Style and Methods

• Structured and analytical approach to problem-solving.
• Ability to transform complex challenges into practical, scalable solutions.
• Strong collaboration skills with both technical and non-technical stakeholders.
• Clear communication skills and ability to present analytical insights in an actionable way.
• Strong focus on quality, reusability and continuous improvement.

Personality

• Curious and eager to learn new technologies and methodologies.
• Proactive, collaborative and solution-oriented mindset.
• Strong sense of ownership and accountability.
• Passion for data, innovation and making a tangible impact in industrial environments.

Additional Information

Work #LikeABosch includes:

⚖️ Flexible work conditions

🔀 Hybrid work system

🌐 Exchange with colleagues around the world

🛡️ Health insurance

🧑‍⚕️ Medical office (psychology and general clinic) & Social Services Office on site

📚 Training opportunities (p.e., technical training, foreign languages training) & certifications

📈 Opportunities for career progression and continuous professional development

💲 Access to great discounts in partnerships and Bosch products

🏋️ Sports and health related activities

🚉 Great access to public transports

🚌 Free transport from Porto

💰 Flexible benefits platform

🅿️ Free parking lot

🍽️ Canteen

What distinguishes you:

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