Sthenos

As a Senior Data Scientist (f/m/d) you assume ownership of various ML models and data workflows within a dynamic team of data scientists, ML engineers and Site Reliability Engineers: 

• You own the End-to-End development of ML solutions from the gathering of business requirements down to the deployment of the solutions on the target infrastructure  

• As a Senior Data Scientist, you act as a thought leader when it comes to designing generic components for recurring activities in the data science lifecycle  

• You actively support the business development of the AI solutions  

• You always keep an eye on the end-to-end ML development process and how this affects the final product  

• You present the technical results of the team precisely but at the same time in a recipient appropriate way  

• In close cooperation with the ML engineers, you further develop the analytical and ML capabilities of the company’s platform and make it ready for the future 

• You independently screen the market of data science solutions, tools and technologies and promote their active testing  

• You actively shape the data science development method in the sense of an ML-Ops target operating model 

• You participate in internal meetups and external conferences to share your achievements with us with the world 

YOUR SKILLS 

• Graduate degree in Computer Science, Statistics, Informatics or another quantitative field 

• 5+ years of experience in data science / machine learning / artificial intelligence.    

• Strong proficiency in Python and its libraries (e.g., Pandas, NumPy, PyTorch, Keras, etc.) 

• First professional experience in following the end-to-end development of AI products including its operations and how performance of ML models can be monitored in real time (ML-Ops) 

• Strong foundational knowledge and proven track record of working with various data storage formats (e.g., Parquet, Avro, ORC, JSON, CSV) and knowledge of the pros and cons of each one 

• Professional experience with data processing frameworks like Spark or Ray 

• Familiarity with the consumption and integration with APIs within data pipelines 

• Knowledge of cloud platforms (e.g., AWS, Azure, GCP) is advantageous  

• Ideally knowledge and experience working with computer vision models, large language models and other modern AI techniques.