We’re building a statistically rigorous, transparent platform for understanding complex audience data. It gets to the heart of what people really think - turning messy human responses into reliable, quantifiable insights. Our architecture combines statistical frameworks with machine learning and large language models, ensuring reproducible results, protection against hallucinations, and consistent quality at scale.
We’ve secured a competitive deep-tech EU grant and are closing a £750k pre-seed round led by a specialist AI fund. We’re already working with major universities, marketing agencies, professional services firms and private equity groups. Now we’re moving from prototype to production, scaling our first deployments and building the scientific foundation for what comes next. As one of our first hires, you’ll help shape WholeSum’s methodology, culture, and future.
For too long, organisations have settled for glorified word clouds, crude sentiment tracking or unreliable AI summaries. We're changing that, making complex human data an asset and not a burden. This is a hard, meaningful problem – come help us solve it.
We’re hiring an Applied Scientist to invent and validate new methods for turning human language into trustworthy insight. You’ll explore the frontier between statistical inference and large language models – designing experiments, prototyping algorithms, and collaborating with engineers to bring your best ideas into production quickly.
You’ll work directly with our CTO – a mathematician with deep experience of turning complex data into real-world impact – and collaborate with enterprise clients to ensure our analysis is rigorous, scalable, and genuinely valuable.
You have a strong background in statistical inference, ML, NLP, and experimental design
You’re excellent at pushing methodological boundaries and turning insights into well-designed Python pipelines
You want to move beyond off-the-shelf LLM and RAG tools, developing innovations that are both original and widely used
You’re excited by the challenge of making messy human data trustworthy and actionable
You care about generating analysis that is accurate, transparent, and impactful
Experience developing and extending machine learning methods for natural language data
Interest in AI reproducibility and auditability
Understanding of survey and sampling methodology
Experience building in early-stage or startup environments
£70,000-£85,000