Lufthansa Technik - Data Scientist

Roles & responsibilities:

Delivery of Key Projects:

• Successfully deliver advanced analytics and data science projects within predefined timelines and budget constraints.

Collaboration:

• Collaborate effectively with data engineers and ML engineers to comprehend data and models, utilizing various advanced analytics capabilities.

Solution Development:

• Develop efficient solutions for complex problems, showcasing expertise in data structures like Delta/Parquet, databases, data analytics, Python programming, and statistics.

End-to-End Pipeline Management:

• Manage the entire data science pipeline, including problem scoping, data gathering, modeling, insights generation, visualizations, monitoring, and maintenance.

Dashboard Design:

• Design dashboards using Python Dash (plotly) or Flask framework for effective data visualization and reporting.

Technological Expertise:

• Utilize CI/CD tools, data pipeline technologies, and visualization/data storytelling tools proficiently.

ETL Pipeline Building:

• Construct ETL pipelines using Python or Azure Synapse to facilitate efficient data processing and management.

Data Procurement and Management:

• Independently procure and process data, ensuring seamless integration within the company's overall data management strategy.

Technology Exploration:

• Continuously monitor advancements in artificial intelligence technology and identify applications for problem-solving within the company.

Technical Skills:

• Proficiency in Python and common libraries (Dash, Pandas, Scikit-Learn, Pydantic, TensorFlow).
• Strong knowledge of statistics and Probability.
• Set up cloud alerts, monitors, dashboards, and logging systems; troubleshoot data platform infrastructure as needed.
• Experience in OpenShift/Kubernetes and Azure ML is desirable.
• Proficiency in programming languages: Python (Dash) and database query languages SQL or KQL.
• Good applied statistical skills, including hands-on experience in time series modeling, predictive modeling, distributions, and regression.
• Knowledge of DevOps/MLOps.
• Exceptional analytical and problem-solving skills.

Preferred candidate profile:

• Bachelor's or Master's degree in Computer Science or a related technical field, or equivalent experience.
• Total of 4 - 8 years of professional experience.
• Minimum of 4 years of experience in data science/machine learning.
• Minimum 3 years of experience with SQL.
• Experience in DevOps, preferably with hands-on experience in one or more cloud service providers, with Azure preferred.