Data Analyst AI Enhanced Analytics

Key Responsibilities: Analytics \u0026amp; AI (core focus) Perform exploratory data analysis (EDA) on HR datasets to uncover trends, drivers, and anomalies. Use AI enabled analytics tools and Python based methods to accelerate data exploration and insight generation. Translate business questions into analytical hypotheses and investigations. Interpret analytical and model outputs, including assumptions, limitations, and uncertainty. Ensure reproducibility, transparency, and documentation of analytical work. Insight Communication \u0026amp; Decision Support Prepare clear analytical outputs and visualizations to communicate findings to stakeholders. Support the definition of KPIs and analytical concepts for management decision making. Translate analytical results into clear recommendations for HR leadership. Data \u0026amp; Delivery Enablement Clean, structure, and validate data from multiple HR systems. Contribute to dashboard and reporting solutions (Power BI, SAC) in collaboration with delivery teams. Ensure compliance with data protection, Works Council, and regulatory requirements (e.g. GDPR). Identify improvement opportunities in HR processes based on data insights. Contribute to HR analytics standards, templates, and best practices. Support the continuous development of the HR Analytics team. Must Have Strong data understanding and analytical thinking, with the ability to structure problems and ask the right questions. Hands\u2011on experience with Python and SQL for data analysis, exploration, and automation. Experience working with AI\u2011enabled analytics or advanced analytical methods, e.g. using AI features in BI tools, applying Python\u2011based analytics, or contributing to AI\u2011supported use cases. Solid understanding of statistics fundamentals (e.g. bias, correlation vs. causation, basic experimentation concepts). Ability to interpret analytical results and model outputs, including limitations and confidence. Experience with data visualization tools (e.g. Power BI) to communicate insights effectively. Strong communication skills and ability to explain analytical findings in plain language. Strong data quality mindset with attention to validation and documentation. Experience working with sensitive data and high confidentiality standards. Very good English skills; German is an advantage. Nice to Have / Can Be Developed Hands\u2011on experience building or applying ML/AI techniques (e.g. forecasting, clustering, classification, NLP). Deeper HR domain knowledge (e.g. workforce planning, talent, learning, engagement). Experience with HR systems and data models (e.g. SAP SuccessFactors, Employee Central, SNOW, Eightfold, CHRIS). Experience with skills/taxonomy data and skill management approaches. Experience leading end\u2011to\u2011end analytics or dashboard projects. Knowledge of HR compliance topics (e.g. GDPR, Works Council processes). Exposure to CSRD and implications for HR data and HRIT. Experience contributing to responsible AI practices beyond basic usage.