Data Science Intern (all genders)

About this role

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. 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. 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.

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. Currently pursuing a degree in Data Science, Computer Science, Physics, Mathematics or a related technical field, with at least three completed semesters.