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2 statistics jobs found in Munich

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Rodenstock GmbH
21/04/2026
Full time
Data Analytics & Business Intelligence Specialist for Germany (m/f/d)
Rodenstock GmbH Elsenheimerstraße 33, 80687 Munich-Laim, Germany
Do you see freedom as an opportunity to explore new paths? Do you say what you think and do what you say? Are you driven by success to take on new challenges and master them with passion? Then you've come to the right place! DATA ANALYTICS & BUSINESS INTELLIGENCE SPECIALIST FOR GERMANY (M/F/D) Your tasks Participation in data and reporting activities for sales in Germany Ensuring data quality, consistency of reporting and transparency throughout Germany Collection, processing and consolidation of sales data from various systems into structured reports and dashboards Tracking sales performance against targets to identify performance deviations early, including following up on defined countermeasures. Creation and maintenance of standardized KPI reports for sales management, team leaders and sales operations. Support with forecasts, performance monitoring and ad-hoc analyses for operational management Providing analytical insights and data inputs for...
autonomous-teaming
22/04/2026
Full time
ML Data Engineer (m/f/d) - Sensor Data & Pipelines
autonomous-teaming 80807 Munich, Germany
What we offer Work in an international, agile team creating the future of autonomous systems Grow your career in a expanding and ambitious engineering team Build innovative products using state-of-the-art technologies in AI, robotics, and autonomy Benefit from a steep learning curve and continuous development Enjoy team events and a strong, collaborative culture Your mission This role sits at the core of our perception systems, owning the data that directly drives model performance in real-world environments. You will work closely with ML, perception, and robotics teams, focusing on   building, curating, and continuously improving datasets behind object detection   — turning raw sensor data into reliable, high-performing systems. You will take   end-to-end ownership of the ML data lifecycle , from data collection and ingestion to labeling, quality assurance, and continuous dataset improvement, ensuring data is representative, high-quality, and...
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