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What you can look forward to as Data Analytics in Technical Project Management (m/f/d): • Create, deploy, and operate Data Analyst Solutions as part of our technical Project Management Team in the context of a cross-functional, agile product team • Develop data-driven services to improve our technical Project Management during Planning, Coordination, and reporting of technical projects • Become a key contact person for data related issues regarding analysis and optimization of our technical Project management processes • Usage of Databank (e.g., PTC integrity, SAP, cplace, Codebeamer) information for reports and visualization • Continuously monitor new developments in the expert field and connect with the internal and external data science community as well as external technology providers, universities etc. • Ideally some years of professional experience in the field of statistics, working as a Advanced Data Analyst with strong data engineering and Visualization skills. • Experience with big data analyses and Databases for data collection will be an advantage Your profile as Data Analytics in Technical Project Management (m/f/d): • Very strong and deep knowledge of Python and relevant libraries for automation and other purposes. • Very strong knowledge of Data analyzing, Data cleaning and other data preprocess as a part of Data Analyst • Very strong and deep knowledge in Visualization Tools such as Power BI , Power App, Power Automate and Tableau for Interactive Dashboard creation • Very strong and deep knowledge of handling various data related tools such as Power Query, DAX Query & Automation of Reports, python scripts from various Data Sources using tools such as Jenkins, SQL • Good knowledge of JIRA software tool with SCRUM framework, AGILE framework & Good knowledge of Share point concept, Share point list etc., • Deep understanding of Bringing Actionable insights from raw data to Dashboard as well as monitoring, troubleshooting, and maintaining existing dashboards and data science solutions & Hands-on Experience in Data Mining, Feature Engineering