Data scientist

Role purpose: Design, build, and deploy AI solutions that improve products and business processes, with a focus on measurable outcomes, reliability, and responsible AI practices. Core responsibilities - Develop and optimize machine learning and/or generative AI models for real-world use cases. - Collect, clean, and analyze data; define features, labels, and evaluation metrics. - Build end-to-end pipelines for training, validation, deployment, and monitoring. - Integrate AI capabilities into applications via APIs and scalable services. - Conduct experimentation (A/B tests), performance tuning, and error analysis. - Document models, assumptions, and decisions; communicate results to stakeholders. - Ensure compliance with security, privacy, and responsible AI standards. Required skills - Strong proficiency in Python and common AI/ML libraries (e.g., PyTorch, TensorFlow, scikit-learn). - Experience with LLMs, prompt engineering, retrieval-augmented generation, or fine-tuning. - Solid

understanding of statistics, model evaluation, and ML best practices. - Data skills: SQL, data wrangling, and working with structured/unstructured data. - Deployment and MLOps experience (CI/CD, containers, model monitoring). - Ability to translate business requirements into technical solutions. Success measures - Delivered AI features that improve key metrics (quality, cost, speed, or revenue). - Reliable production performance with monitoring, retraining, and clear documentation. Als AI Specialist (intern functienaam...