Data Analyst m/f/d

  • ATOSS Software
  • 81829 München, Germany
  • 27/05/2024
Full time Data Analytics Artificial Intelligence Software Engineering Data Warehouse

Job Description

Your Responsibilities:
  • Full Lifecycle Analysis : Conduct requirements gathering, design, and analysis activities. Develop robust analysis and reporting capabilities, monitoring performance, and quality control plans to identify improvements.
  • Data Management : Define, design, and implement scalable data collection, processing and storage procedures to enable comprehensive insights and powerful reporting capabilities, essential for building analytic systems.
  • Data Governance : Establish strong data governance processes to ensure data integrity, accuracy, and compliance with relevant legal regulations.
  • Trend Analysis : Identify, analyze, and interpret trends or patterns in complex data sets using statistical techniques, providing ongoing reports.
  • Automated Systems : Create automated anomaly detection systems and continuously track their performance.
  • Data Models : Develop strong domain knowledge and design comprehensive foundational data models to power all data-driven experiences and capabilities within the product.
  • Advanced Tools : Leverage best-in-class data analysis and reporting tools to automate the generation of key trends, patterns, and insights swiftly.
  • Strategic Boost : Drive the data strategy to enhance AI and ML capabilities within our product portfolio. Collaborate with R&D to conceptualize a scalable data-to-insights framework.
  • Ad-Hoc Analysis : Conduct ad-hoc analysis and present results clearly and effectively.
  • Prioritization : Work with management to prioritize business and information needs.
Your Skills and Expertise:
  • Experience : Proven 5-7 years of working experience as a Data Analyst or Data Scientist. Solid experience in data analysis with proficiency in SQL, Python, and R for data manipulation and statistical analysis.
  • Technical Expertise : Strong expertise in data models, database design development, data mining, and segmentation techniques.
  • Reporting Packages : Proficient with reporting packages (eg, Business Objects), databases (eg, SQL), and programming (eg, XML, JavaScript, ETL frameworks).
  • Analytics Tools : Hands-on expertise in using state-of-the-art tools such as Tableau, Power BI, Qlik, Knime, RapidMiner, DataIQ, Jupyter AI, and statistical tools (eg, Excel, SPSS, SAS, SQL queries).
  • Machine Learning & AI: Familiarity with machine learning frameworks like TensorFlow, Keras, or scikit-learn for developing predictive models and algorithms. Experience with low-code no-code AI data analysis tools like RapidMiner, DataIQ or Knime.
  • Data Engineering: Experience with big data technologies such as Hadoop, Spark, and Kafka for efficient data processing and pipeline creation.
  • Cloud Platforms : Knowledge of cloud-based analytics services such as AWS, Google Cloud Platform, and Azure.
  • Analytical Skills: Exceptional ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
  • Communication : Excellent communication skills to convey findings to stakeholders clearly, explaining reasoning and research to justify conclusions.
  • Education : Master's degree in Mathematics, Economics, Computer Science, Information Management, or Statistics.
  • Problem-Solving : Exceptional analytical and problem-solving abilities, with a keen eye for detail and a passion for uncovering hidden insights.