(Senior) Data Scientist, People Analytics & Intelligence (m/f/d)

We're looking for a pragmatic, hands-on Data Scientist to join our People Analytics & Intelligence team and drive the data-driven transformation of our HR organization. You're the person who doesn't just build models but knows how to deliver real business impact through end-to-end solutions.

Responsibilities

• Analytics & Insights – Translate complex business questions into actionable data analyses and visualize results to enable business decisions.

  Develop models and analyses on topics along the employee life cycle (e.g., hiring, talent identification and development, retention and workforce planning).

  Conduct statistical analyses (e.g., regression, clustering, causal inference) and explain findings in ways non-technical stakeholders can understand.

  Experiment with emerging technologies for sentiment analysis and automated insights generation.

• End-to-End Implementation – Work with various data sources (HRIS, payroll & time management, ATS, survey tools, etc.) and integrate them into our analytics ecosystem.

  Help to optimize our data infrastructure – from ETL pipelines, data preparation to data modeling.

  Ensure data quality, governance standards, and develop automated data validation processes.

  Automate recurring reporting to create capacity for strategic analysis.

  Develop self‑service solutions (dashboards, conversational GenAI) that empower HR and business leaders to make data‑driven decisions.

  Implement best practices in code documentation, version control, and testing.

Qualifications

• Master’s Degree or PhD in Computer Science, Mathematics, Statistics, Psychology, Information Systems, or related field; or Bachelor’s with 5+ years of relevant experience.
• 3+ years of hands‑on experience in Data Science/Analytics, ideally with HR focus.
• Strong programming skills in Python (required); experience with R is a plus, combined with solid statistical expertise.
• Working knowledge of SQL and relational databases, with the ability to query, extract, and understand structured data.
• Experience creating data visualizations and dashboards using Python/R frameworks (e.g., Pandas, PySpark) and BI platforms (e.g., Power BI).
• Pragmatic "get‑things‑done" mentality.
• Fluent in English; German is a plus.
• Preferred: Experience with modern data platforms such as Databricks and Microsoft Azure; familiarity with enterprise data environments (e.g., SAP Datasphere), data preparation, feature engineering, and agile ways of working.