Lufthansa Technik Services - Data Scientist - Python/Statistical Analysis

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 to 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.