AI, Python Engineer (m/f/d)

Job Description Job Description – Data Analytics & Data Science Specialist Key Responsibilities: Analyze, assess, and interpret large datasets using advanced analytics techniques on modern data platforms. Prepare reports, dashboards, and insights to support business decision-making. Evaluate data structures, data quality, and business processes to identify improvement opportunities. Design, develop, and maintain effective data models to support analytical and operational requirements. Apply machine learning techniques and integrate analytical outcomes into business solutions and processes. Perform data transformation activities including data enrichment, blending, expansion, filtering, consolidation, and cleansing. Prepare cost-benefit analyses and support techno-economic evaluations for data-driven initiatives. Develop and present recommendations, decision-making proposals, and actionable insights to stakeholders. Participate in the development of assessment, monitoring, and steering tools for handling multiple data sources and ensuring data availability. Manage end-to-end analytics and data science projects, ensuring timely delivery and alignment with business objectives. Collaborate with cross-functional teams to implement data-driven solutions and drive continuous improvement. Required Skills & Qualifications Strong experience in Data Analytics, Data Science, or related fields. Hands-on experience with data modeling, data transformation, and data management techniques. Knowledge of Machine Learning, Statistical Analysis, and Predictive Modeling. Experience working with modern data platforms such as Azure, AWS, Google Cloud, Databricks, Snowflake, or similar. Proficiency in SQL and programming languages such as Python or R. Experience with data visualization and reporting tools such as Power BI, Tableau, or equivalent. Strong analytical, problem-solving, and stakeholder management skills. Experience managing analytics or data-driven projects. Preferred Qualifications Experience in cloud-based data ecosystems and big data technologies. Understanding of data governance, data quality, and data architecture principles. Certifications in Data Analytics, Data Science, Machine Learning, Azure, AWS, or related technologies are an advantage.