Working Student Computer Vision Engineer

STARK

ABOUT US STARK is a new kind of defence technology company revolutionising the way autonomous systems are deployed across multiple domains. We design, develop and manufacture high-performance unmanned systems that are software-defined, mass-scalable and cost-effective. This provides our operators with a decisive edge in highly contested environments. We’re focused on delivering deployable, high-performance systems—not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe—today. ABOUT THE TEAM The Flight Science team is responsible for analysing, processing and interpreting data generated throughout the development and testing of our autonomous systems. By building reliable data infrastructure and scalable analytics workflows, the team enables engineers to make informed decisions that improve system performance, reliability and operational capability. Working closely with software, robotics and flight test engineers, the team transforms complex engineering data into actionable insights that drive product development YOUR MISSION As a Data Engineering Intern / Working Student, you will help build and maintain the data infrastructure that powers the Flight Science team's analytics and decision-making. You will develop reliable data pipelines, improve data quality and collaborate with engineers to ensure flight and operational data is accessible, accurate and scalable. RESPONSIBILITIES * Develop and maintain automated ETL/ELT pipelines to ingest, clean and structure raw flight test and simulation data. * Optimise data workflows to reduce processing latency and improve access to engineering analytics. * Implement data validation and monitoring processes to identify pipeline failures, anomalies and missing data. * Collaborate with Flight Science engineers to design scalable data models and database schemas. * Integrate new internal and external data sources, including weather and telemetry datasets. * Document pipeline architecture, data models and system dependencies to support maintainability and knowledge sharing. * Support the scaling and optimisation of data storage solutions as flight data volumes increase. QUALIFICATIONS * Currently pursuing a degree in Computer Science, Information Systems, Data Science or a related technical field, with at least three completed semesters. * Strong Python programming skills for data processing and scripting. * Solid understanding of SQL and relational databases. * Familiarity with ETL/ELT concepts and data pipeline development through university projects, internships or personal projects. * Experience using Git or other version control systems. * Strong English communication skills, both written and spoken. * Availability to work full-time for a six-month internship or part-time (15–20 hours per week) as a working student. NICE TO HAVE * Experience working with time-series or sensor data. * Familiarity with workflow orchestration tools such as Apache Airflow or Prefect. * Basic knowledge of cloud platforms (AWS, Azure or GCP) or Docker. * Experience with data visualisation tools such as Grafana, Tableau or Streamlit.

STARK

ABOUT US STARK is a new kind of defence technology company revolutionising the way autonomous systems are deployed across multiple domains. We design, develop and manufacture high-performance unmanned systems that are software-defined, mass-scalable and cost-effective. This provides our operators with a decisive edge in highly contested environments. We’re focused on delivering deployable, high-performance systems—not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe—today. ABOUT THE TEAM The Flight Science team is responsible for analysing, processing and interpreting data generated throughout the development and testing of our autonomous systems. By combining advanced analytics, statistical modelling and engineering expertise, the team transforms complex flight and operational data into actionable insights that improve system performance, reliability and operational capability. Working closely with software, robotics and flight test engineers, the team supports data-driven decision making across the product development lifecycle. YOUR MISSION As a Data Science Intern / Working Student, you will analyse flight and operational data to generate insights that improve the performance of our autonomous systems. You will develop predictive models, perform statistical analysis and collaborate with engineers to transform complex sensor data into meaningful recommendations that support engineering decisions. RESPONSIBILITIES * Perform exploratory data analysis to identify patterns, trends and anomalies within flight test and operational data. * Develop, train and evaluate predictive models and statistical algorithms to support engineering and product development. * Create visualisations and reports that communicate technical findings clearly to engineering stakeholders. * Collaborate with Flight Science engineers to design experiments and validate hypotheses using real-world sensor data. * Develop data processing workflows to prepare and enrich datasets for modelling and analysis. * Document methodologies, experiments and analytical results to support knowledge sharing and reproducibility. * Support the evaluation of performance metrics for software-defined features and autonomous system capabilities. QUALIFICATIONS * Currently pursuing a degree in Data Science, Computer Science, Physics, Mathematics or a related technical field, with at least three completed semesters. * Strong Python programming skills for data analysis and machine learning. * Solid understanding of statistics and machine learning fundamentals. * Experience using SQL to query and manage relational databases. * Familiarity with data visualisation libraries such as Matplotlib or Plotly, or comparable BI tools. * Experience using Git or other version control systems. * Strong English communication skills, both written and spoken. * Availability to work full-time for a six-month internship or part-time (15–20 hours per week) as a working student. NICE TO HAVE * Experience with deep learning frameworks such as PyTorch or TensorFlow. * Familiarity with time-series analysis, sensor data or signal processing. * Basic knowledge of cloud platforms (AWS, Azure or GCP) or Docker. * Experience translating complex analytical findings into practical recommendations for technical or business stakeholders.

Staburo

YOUR RESPONSIBILITIES WILL INCLUDE * Hands-on data processing and analysis of clinical data (e.g., trial data, biomarkers, gene expression data) * Support in Data Science projects as well as non-clinical / clinical development in all study phases, e.g., programming of tables and figures, sample size calculation, high-dimensional data analysis * Data visualization and output generation * Statistical programming and development of reusable programs (e.g., functions, macros, R packages) YOUR PROFILE * Studies in statistics, mathematics, data science, or a similar direction  * Knowledge on basic and advanced statistical methods, e.g., hypothesis testing, multivariate analysis * Advanced programming skills in R, knowledge in R Shiny Applications optional * Strong analytical and quick-learning skills  * Precise and accurate way of working  * Team player and a high degree of initiative * Good English skills, German is an advantage * As a working student (f/m/d), you are available for up to 20 hours per week, whereby you can flexibly adjust your working hours to your schedule – starting immediately WHAT WE OFFER YOU We value communication, flat hierarchies, open corporate culture, and a harmonious work environment. We offer comprehensive individual development opportunities, even after your studies, continuous trainings, and flexible working hours. A modern and bright office with a subsidised canteen is part of our everyday working life. You will join an interdisciplinary team allowing you to discuss with and learn from peers with many different backgrounds. QUESTION? If you have any questions, please feel free to contact us by e-mail application@staburo.de.