WebMD is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, ancestry, color, religion, sex, gender, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.
As a Data Scientist / Machine Learning Engineer (m/f/d) you are responsible for developing end-to-end machine learning solutions that transform complex, unstructured data into actionable business insights. You work across the full ML lifecycle, from data acquisition and experimentation to production deployment, with a focus on NLP, document intelligence, LLM-powered applications, and predictive analytics.
You decide where you work: Germany-wide from your home office, at one of our locations in Constance or Munich, or in a hybrid setup.
As a Data Scientist, you design and implement data-driven solutions that solve real-world business problems. You develop automated ML pipelines, build robust data processing workflows, and evaluate model performance using quantitative experimentation.
You collaborate closely with Data Engineering, Product, and Business teams to deliver production-ready machine learning systems and communicate technical findings to both technical and non-technical stakeholders.
You are responsible for:
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Designing end-to-end machine learning pipelines from proof of concept to production.
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Building document intelligence and information extraction systems using modern LLMs.
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Developing automated data processing workflows for structured and unstructured datasets.
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Designing evaluation frameworks and statistical experiments to measure model performance.
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Performing structured error analysis to identify model limitations and improve solution quality.
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Supporting AI adoption by integrating state-of-the-art generative AI technologies into business workflows.
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Collaborating with cross-functional teams and industry partners to deliver measurable business impact.
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4+ years of professional experience as a Data Scientist or Machine Learning Engineer.
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Excellent Python programming skills with experience using Pandas, NumPy, Scikit-learn, and modern ML tooling.
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Experience building production-ready machine learning pipelines using LLMs, NLP, computer vision, or predictive modelling.
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Hands-on experience with GPT models, document intelligence, OCR pipelines, and structured information extraction.
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Strong experience designing model evaluation frameworks, statistical analysis, and experiment design.
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Experience working with cloud infrastructure (AWS), containerised deployments, and production ML workflows.
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Solid SQL and data engineering skills with experience processing large-scale structured and unstructured datasets.
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Experience communicating technical results to business stakeholders and collaborating with multidisciplinary teams.
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Strong problem-solving skills with a pragmatic, customer-focused mindset.
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Experience with Retrieval-Augmented Generation (RAG) systems.
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Experience with computer vision or speech recognition applications.
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Experience using Pydantic, ONNX, Docker, and modern LLM frameworks.
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Experience working with healthcare or industry data.
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Flexible remote and hybrid working options.
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Opportunities to build production AI systems with real business impact.
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Cross-functional collaboration with experts in Data Science, Engineering, and Product.
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Modern cloud infrastructure and access to state-of-the-art AI technologies.
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Strong focus on innovation, experimentation, and continuous learning.
