Senior Data Scientist

Are you excited to turn complex business questions into measurable impact? We are hiring a Senior Data Scientist for the Machine Learning & Artificial Intelligence unit within Bayer’s Enterprise Data & Analytics Platform. You will combine generative AI with classical machine learning, lead rigorous experimentation and evaluation, and communicate clear, actionable insights to stakeholders- delivering high-impact AI solutions across Finance, Supply Chain, HR, Procurement, Legal, and Communications. Our international team spans Poland, Germany, Spain, and India. We work with LLMs and embeddings, classical ML, and optimization on a modern, cloud-native stack (Python, AWS, Azure, Databricks). If solving business problems with analytical rigor and applying cutting-edge machine learning and GenAI techniques excites you, this is the place.

At Bayer, we are committed to transparency, equal pay for equal work or work of equal value, and objective reward practices in line with EU and local regulations. The minimum annual gross compensation for this role is 20 240 PLN, with final pay determined based on objective factors such as experience, qualifications, scope of responsibility, and internal alignment.

This position is eligible for variable pay components, such as performance based bonuses, awarded in accordance with the applicable employee group, role scope, and compensation structure.

• Master’s or PhD with 5+ years in Data Science or Applied ML, delivering production-impact solutions.
• Strong Python and SQL skills; expertise with standard data science libraries: pandas, NumPy, scikit-learn; experience with PyTorch or TensorFlow is a plus.
• Hands-on with Generative AI: embeddings, prompt engineering, tool/function calling, and agent frameworks (LangChain, LangGraph, PydanticAI); experience with vector databases (pgvector and others).
• Solid grounding in classical ML: model selection, validation, and metrics (e.g., AUC/F1/RMSE); time series or forecasting experience is a plus.
• Evaluation focus: design and run offline/online tests, rubric-based GenAI evaluation, safety checks, and error analysis; familiarity with LangSmith/Langfuse or similar is beneficial.
• Clear stakeholder communication: requirements gathering, expectation setting, storytelling, and influencing decisions with data.
• Proven problem-solving skills: structuring ambiguous problems, hypothesis-driven analysis, and iterative experimentation.
• Basic cloud proficiency (AWS and/or Azure): storage and compute (e.g., S3/Blob, Lambda/Functions or containers), secrets, and Databricks or Spark; awareness of CI/CD (e.g., GitHub Actions).
• Good engineering hygiene: modular code, testing, documentation, and reproducibility.
• Data governance and privacy awareness.
• Fluent in English (written and spoken); additional languages from our team regions are a plus.