Sthenos AI is the AI developer of EFA Group, building intelligent, mission-ready solutions for defense and aerospace. With deep expertise in Command-and-Control (C2), cyber defense, computer vision, and autonomous systems, we design and deploy secure, field-proven AI that enhances operational efficiency and situational awareness. As part of a leading European defense ecosystem, we bring scalable innovation where it matters most — in the theater of operations.
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.
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