3 statistics jobs found in Munich

Are you passionate about leading teams and delivering top-notch IT solutions for clients? As a leader with strong communication skills and a vision for a high-performance team, you will actively shape the future of our Atlassian and cloud projects as a Consulting Team Lead (m/f/d) at XALT. XALT Business Consulting GmbH is an Atlassian Platinum Solution Partner with 100% DevSecOps DNA and implements projects in areas such as ITSM, social intranets, cloud infrastructure, and identity management Team Leadership & Delivery: Professional and organizational management of the consulting team – planning the deployment of consultants in Atlassian and DevOps projects and ensuring timely, high-quality results as well as satisfied customers. Methodology & Processes: Definition and optimization of our consulting processes and best practices within the team, as well as the establishment of appropriate methods and continuous improvements. Customer escalations: Direct...

Location(s):  Cologne  ,  Mannheim  ,  Munich, Nuremberg, Stuttgart Type:  Permanent position, full-time, part-time and mobile working If you're looking for a job that offers you true flexibility and values ​​your professional excellence, we'd like to introduce you to the following position. At bridgingIT,  people are our priority  , and  now it's your turn! YOUR role Shape the future of data with us! Whether you're a beginner or an experienced professional – if you love data and want to create real value from it, you've come to the right place. With us, you can contribute your expertise, develop it further, and work with our team to create innovative solutions. Become part of our analytics and data community and collaborate with like-minded individuals on exciting projects. Data Engineering: Data processing & architecture  : Conception and development of ETL/ELT pipelines (e.g. on...

Your mission Design and maintain scalable pipelines to ingest and organize large volumes of time-series camera and sensor data (RGB, IR, acoustic, depth, IMU, and other modalities). Own and improve datasets for object detection and classification tasks, ensuring statistical robustness, diversity, and representativeness. Build and operate active learning loops to select high-value samples, reduce annotation cost, and continuously improve model performance. Write robust preprocessing pipelines using Python, NumPy, Pandas, and augmentation libraries like Albumentations. Manage labeling workflows, including QA rules, label consistency checks, vendor coordination, and dataset versioning. Collaborate with ML Engineers to fine-tune, train, and evaluate object detection models and feed insights back into the data pipeline. Analyze model weaknesses, uncover blind spots, and drive dataset improvements through statistical diagnostics and drift/bias detection. Create...