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About the Role
Develop data-driven solutions and machine learning applications for various business areas, from data analysis and model development to operationalization, working closely with business departments, data engineering, software development, and IT.
Responsibilities
- Analyze large datasets to identify relevant patterns, trends, and business potentials.
- Develop, train, validate, and optimize machine learning models for forecasts, classifications, clustering, and optimization tasks.
- Conduct model evaluations, experiments, and analyses to continuously improve prediction quality.
- Develop proofs of concept and transition suitable solutions into productive use with involved teams.
- Support the deployment, monitoring, and retraining of machine learning models.
- Ensure data and model quality, including comprehensible documentation and ongoing monitoring.
- Identify and prioritize suitable use cases in collaboration with business departments, data engineering, software development, and IT.
- Prepare analysis results and recommendations understandably and present them to both technical and non-technical stakeholders.
- Stay updated on current developments in data science and machine learning, evaluating the suitability of technologies and approaches for requirements.
Requirements
- Completed degree in Computer Science, Mathematics, Statistics, Data Science, or a comparable qualification with relevant practical experience.
- Several years of practical experience in data science and machine learning, ideally around 3-5 years.
- Very good knowledge of Python and experience with relevant libraries and frameworks such as Pandas, NumPy, Scikit-Learn, TensorFlow, or PyTorch.
- Good knowledge of SQL and experience with data modeling and processing of structured and unstructured data.
- Good understanding of statistics, probability theory, and model evaluation methods.
- Practical experience with machine learning methods for forecasts, classifications, clustering, or optimizations.
- Experience working with large datasets and knowledge of modern data platforms and data pipelines.
- Experience in deploying machine learning models into production, including deployment, monitoring, and retraining.
- Analytical, structured, and solution-oriented work approach.
- Ability to explain complex contexts understandably.
- Confident communication in German and English.
Skills
- Python
- Pandas
- NumPy
- Scikit-Learn
- TensorFlow
- PyTorch
- SQL
- Data Modeling
- Machine Learning
- Data Analysis
- Statistics
- Probability Theory
- Model Evaluation
- Data Pipelines
Location
- Berlin Kreuzberg
Work Type
- Home Office
- Workation
Experience Level
- 3-5 years
Education Level
- Degree in Computer Science, Mathematics, Statistics, Data Science, or comparable qualification
Benefits
- Flexible home office arrangement
- Up to 30 days of workation per year
- Free, freshly cooked organic and regional lunch daily
- Public transport subsidy of 50 Euros per month
- Company pension scheme contribution
- Weekly massage service (partially employer-funded)
- Numerous team and company events
- Industry-standard discounts for travel
- Opportunities to contribute to sustainability initiatives
About the Company
- The AERTiCKET Group is one of the world's largest full-service consolidators and independent business-to-business service providers for scheduled flights.
- We are partners to airlines and service providers for travel agencies, tour operators, cooperations, and portals.
- Our experienced fare specialists are available to our customers 24/7, 365 days a year.
- We develop state-of-the-art booking technologies for the future of the travel industry, providing a decisive competitive advantage.
- Our group employs approximately 850 people from 28 nations at 40 locations worldwide.
- In Germany, we have offices in Berlin-Kreuzberg (headquarters), Frankfurt/Main, Hanover, Hamburg, and Saarlouis.