What distinguishes you:
Education
- 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
