Data Analyst m/f/d

at  ATOSS Software AG

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 (e.g., Business Objects), databases (e.g., SQL), and programming (e.g., 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 (e.g., 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.

• 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.