Applied Scientist at Deep-tech AI data platform

You will bridge the gap between statistical inference and large language models to turn complex human language into reliable, quantifiable insights. Working directly with the CTO, you will design experiments and prototype algorithms that move beyond off-the-shelf tools to create a statistically rigorous foundation for analyzing large-scale audience data.

Deep-tech AI data platform

• Design and prototype Python pipelines that integrate statistical frameworks with machine learning and large language models.
• Collaborate directly with the founders and enterprise clients to ensure analytical rigor and scalability in real-world deployments.
• Explore and implement methods for AI reproducibility and auditability to protect against hallucinations and ensure consistent quality.

• Possesses a strong academic or professional background in statistical inference, machine learning, NLP, and experimental design.
• Demonstrates experience pushing methodological boundaries to turn theoretical insights into well-designed, production-ready software pipelines.
• Thrives in early-stage environments and is motivated by the challenge of making unstructured human data trustworthy and impactful.

• Invent and validate novel methodologies at the frontier of NLP and statistical inference rather than just implementing standard RAG patterns.
• Join an early-stage team backed by a specialist AI fund and prestigious deep-tech grants, moving from prototype to production scale.
• Solve a high-impact, meaningful problem by making messy human data transparent, reproducible, and actionable for global enterprise clients.