Senior Data Scientist, Lunio

• Strong experience designing, deploying, and operating production-grade ML systems, with a proven ability to rapidly prototype ideas and translate them into scalable, production-ready solutions
• Deep proficiency in Python and SQL, with strong experience working with large-scale datasets in cloud environments
• Hands-on experience with LLM-based systems and applied AI workflows, including RAG, agentic architectures, and other NLP techniques
• Strong product and systems thinking, with an eye for scalability, reliability, and explainability
• Practical and pragmatic — able to balance technical depth with speed and business impact

Desirable

• As a Senior Data Scientist Lunio you will help build new capabilities that expand our value proposition and create new ways for customers to understand, detect, and act on ad waste
• You will sit at the intersection of data science, AI, and product development
• You will help identify opportunities to extend our core wasteful traffic prevention product, rapidly prototype new capabilities, and turn promising concepts into production-ready solutions in close collaboration with Engineering and Product
• The role has a strong 0-to-1 component and will involve developing AI systems, and leveraging LLMs, and/or advanced machine learning techniques where they can create meaningful value for our customers and strengthen our product offering
• R&D: Own the discovery and development of new capabilities that expand Lunio’s core wasteful traffic prevention product and strengthen our value proposition for customers, from early prototyping through to production-ready MVP
• Experimentation: Translate customer and product needs into concrete hypotheses, experiments, and POCs, refining solutions as they develop
• Concept-to-Launch Delivery: Work closely with Engineering and Product to take new capabilities from concept through to launch, ensuring successful prototypes are translated into robust, maintainable, production-ready solutions
• Pragmatic ML & AI Application: Apply machine learning and AI techniques pragmatically, focusing on areas where they deliver clear customer or product value, and carefully balancing implementation effort against expected impact