- Collaborates with Data Scientists to test and scale new algorithms through pilots and later industrializes the solutions at scale
- Influences, contributes and maintains the large-scale data infrastructure required for the AI projects in close collaboration with the data engineers
- Leverages an understanding of software architecture and software design patterns to write scalable, maintainable, well-designed and future-proof code
- Designs, develops and maintains the framework for analytical pipeline
- Develops common components to address pain points in machine learning project, like model lifecycle management, feature store and data quality evaluation
- Provides input and helps implement frameworks and tools to improve data quality
- Works in cross-functional agile teams to build the AI ecosystem within the Group
- Delivers on time, demonstrating strong commitment to deliver on the team mission and agreed backlog
- Has a background in computer science, mathematics or related technical discipline
- Is experienced in software engineering with exposure to statistical and/or data science role
- Has deep knowledge and proven experience with optimizing machine learning model in a production context
- Worked with Python or Scala in a productive environment (mandatory). Background in programming in C, C++, Java is beneficial
- Exposure to both streaming and non-streaming analytics. Experience with SQL, Spark, Pandas, Numpy, SciPy, Statsmodels, Stan, pymc3, Caret, Scikit-learn, Keras, TensorFlow, Pytorch, Databricks is beneficial.
- Has experience working with large data sets, simulation/optimisation and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.)
- Excellent communication skills and business fluency in English; knowledge of German is a plus
Company
Location
Mülheim an der Ruhr - Germany
Job type
Full-Time
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