Senior Data Scientist (f/m/div.)
Aufgaben
We are seeking an experienced Senior Data Scientist to join our team in a P2030 project that will start Q1.2025. As a Senior Data Scientist, you will play a crucial role in organizing and interpreting data to inform decision-makers, and leverage your statistical analysis and machine learning expertise to develop predictive maintenance models. Your expertise will contribute to our global mission, leveraging unique and specialized data sets.
Responsibilities:
• Conduct in-depth data analysis, including data mining and predictive modelling.
• Provide insights to drive successful operations and strategic decisions.
• Design, implement, train, evaluate and optimize machine learning models for predictive maintenance.
• Support the deploy of ML models into production.
• Build solutions to monitor performance of the data pipelines deployed and take corrective measures when necessary.
• Work closely with cross-functional teams to understand business requirements and extract valuable insights.
• Communicate findings to technical and non-technical stakeholders through clear and compelling presentations and reports.
• Take part in innovation projects and collaborate closely with academic institutions.
• Ensure ethical practices in algorithm design and data utilization
Profil Experience:
• Minimum of 5 years in a data science or analytics role.
Technical Skills:
• Proficiency in machine learning model development, evaluation, and optimization. o Knowledge of data preprocessing techniques, feature engineering and feature selection methods.
• Ability to conduct exploratory data analysis to uncover patterns, anomalies and valuable insights.
• Experience with CI/CD pipelines and good software development practices, including version control, code organization and testing.
• Proficiency in Python (e.g. NumPy, Pandas, Scikit-learn, TensorFlow or PyTorch, etc.).
• SQL knowledge for data manipulation and querying.
• Able to work with no-relational databases (e.g. MongoDB)
• Experience with Microsoft Azure cloud platform. o Knowledge in MLOps.
• Experience working in an agile (Scrum or Kanban) framework.
• Experience with Linux OS and Docker. o Ability to share knowledge and mentoring junior team members.
• Good analytical skills.
• Eager to work with the newest technologies.
• High initiative and ability to work independently.
• Solution-oriented, pragmatic, with an eye for detail and capable of explaining decisions and results.
• Evangelist of best practices in ML-based software development.
• Good communication skills.
• Experience with anomaly detection and/or predictive maintenance use cases is a plus.
• Fluent in English.
Education:
• MSc or PhD degree in Data Science, Computer Science, Engineering or equivalent.
Experience:
• Minimum of 5 years in a data science or analytics role.
Technical Skills:
• Proficiency in machine learning model development, evaluation, and optimization. o Knowledge of data preprocessing techniques, feature engineering and feature selection methods.
• Ability to conduct exploratory data analysis to uncover patterns, anomalies and valuable insights.
• Experience with CI/CD pipelines and good software development practices, including version control, code organization and testing.
• Proficiency in Python (e.g. NumPy, Pandas, Scikit-learn, TensorFlow or PyTorch, etc.).
• SQL knowledge for data manipulation and querying.
• Able to work with no-relational databases (e.g. MongoDB)
• Experience with Microsoft Azure cloud platform. o Knowledge in MLOps.
• Experience working in an agile (Scrum or Kanban) framework.
• Experience with Linux OS and Docker. o Ability to share knowledge and mentoring junior team members.
• Good analytical skills.
• Eager to work with the newest technologies.
• High initiative and ability to work independently.
• Solution-oriented, pragmatic, with an eye for detail and capable of explaining decisions and results.
• Evangelist of best practices in ML-based software development.
• Good communication skills.
• Experience with anomaly detection and/or predictive maintenance use cases is a plus.
• Fluent in English.
Education:
• MSc or PhD degree in Data Science, Computer Science, Engineering or equivalent.
