(Senior) Data Analyst (m/f/d)

As a Data Analyst (m/f/d) focussing in the land domain for unmanned ground vehicles, you will play a leading role within the Cloud & Data Team, owning the evaluation, interpretation, and continuous improvement of analytics for large-scale telemetry and system data. You will shape how data is analyzed across products and platforms, enabling data-driven decisions in R&D, production, testing, and customer support. You will work with a highly skilled team and collaborate closely with stakeholders across the globe. In this role, you will combine advanced analytical skills, algorithm development, and technical leadership to build robust, automated evaluation methods for complex technical systems.

What is your Day to Day Mission:

• Lead tool-based analysis of telemetry and system data across R&D, production, testing, and customer support

• Own and evolve the data analysis toolchain, ensuring scalability, reliability, and reproducibility

• Design, implement, and maintain automated data evaluation and testing pipelines

• Drive the design and use of database solutions for large-scale telemetry data

• Evaluate, prototype, and deploy advanced analytics and AI-based methods, including anomaly detection, predictive maintenance, and online monitoring of subsystems

• Collaborate closely with Data Engineers and Cloud Engineers to integrate analytics into production systems

• Communicate insights and analytical results clearly to technical and non-technical stakeholders

• Act as a technical mentor and analytical authority within the team

What you bring to the team:

Data Analysis & Algorithms

• Strong hands-on experience using python for data analysis and algorithm development

• Solid understanding of statistics, hypothesis testing, and data validation techniques

• Experience designing custom evaluation algorithms for complex or high-frequency data

• Strong experience with time-series analysis and telemetry data

Data & Databases

• Experience working with timeseries, structured, unstructured and analytical databases

• Good understanding of efficient data storage, retrieval, and optimization strategies

• Experience collaborating on data models and analytical interfaces

Advanced Analytics

• Experience evaluating or implementing machine learning or AI-based methods (e.g. anomaly detection, predictive maintenance, trend analysis)

• Understanding of model validation, robustness, and monitoring in production contexts

Why