Key skills
AzureCloudKerasNumpyPandasPySparkPythonPyTorchScikit-LearnSQLTensorflowMachine LearningMLDeep LearningTensorFlowscikit-learnNumPyMLflowAnalyticsDatabricksData MiningStatistical AnalysisGitVersion ControlAgileScrumCI/CDCommunicationCollaborationPresentation Skills
About this role
Role Overview
- Apply statistical modeling, machine learning, and deep learning techniques on multivariate time-series data to develop predictive, modular, and scalable condition monitoring systems for wind turbines
- Design and implement robust model management processes to govern the entire ML lifecycle, including development, deployment, and operations, within a cross-functional predictive maintenance architecture
- Define accurate, statistically sound summary metrics to evaluate and benchmark model performance effectively
- Translate complex, statistically rigorous analyses into actionable insights and communicate findings to cross-functional teams, customers, partners, and executives to create measurable business impact
- Work collaboratively within Agile teams comprising Data Scientists, Data Engineers, and Quality Engineers to research, develop, and deliver advanced analytical solutions that create business value
- Interact with domain experts to understand real-world challenges and interpret approaches for practical, impactful solutions
- Research and apply advanced ML techniques to improve prediction accuracy
- Optimize models for scalability and performance in production environments
- Ensure data quality, security, and compliance with organizational standards
- Anticipate internal and external business issues, recommend best practices, and provide strategic guidance on product, process, or service improvements to overcome challenges
- Represent Vestas within the industry and scientific community by building relationships, sharing knowledge, and promoting collaboration among peers
Requirements
- Bachelor's/Master's / PhD in Computer Science / Data Science / Statistics / Mathematics / STEM / Similar specialization
- Minimum 5+ years of experience in Data Science and frameworks, including proficiency with data preparation and data exploration techniques
- Application of machine learning techniques such as data mining, statistical analysis, deep learning, and anomaly detection
- Extensive experience in analyzing large-scale condition monitoring datasets, including SCADA and CMS data, to derive strategic insights
- Professional certification in Vibration Analysis
- Proficient communication & presentation skills in English, both written and verbal
- Advanced proficiency in Python, Pyspark and its libraries (Pandas, NumPy, Scikit-learn, TensorFlow/Keras, PyTorch, MLflow, etc.)
- Experience with SQL and data manipulation
- Solid understanding of machine learning and deep learning algorithms, statistical modeling, and predictive analytics
- Good knowledge of cloud platforms, particularly Azure
- Experience using Databricks for ML workflows and big data processing
- Experience in building and managing CI/CD pipelines for machine learning models
- Knowledge of model deployment, monitoring, and retraining strategies in production environments
- Proficiency with version control systems (Git) & demonstrated ability to collaborate effectively in Scrum teams
- Experience with time-series analysis and forecasting & Solid foundation in probability, statistics, and optimization techniques
- Proficiency in designing and developing end-to-end production-ready ML pipelines using PySpark, Databricks, and cloud platforms
Tech Stack
- Azure
- Cloud
- Keras
- Numpy
- Pandas
- PySpark
- Python
- PyTorch
- Scikit-Learn
- SQL
- Tensorflow
Benefits
- Professional development opportunities
- Work in a multicultural and international company