AI + Data Scientist
Summary
Build and deploy AI models—from forecasting to LLM workflows—using Python, SQL, and GenAI techniques, and ship them to production with engineering teams.
Overview
Build AI that does something useful. We are looking for a sharp Data Scientist who can move comfortably between messy data, proper machine learning and the newer GenAI world. You will take real business problems, find the signal, build the model or AI workflow, and get it into production.
One week you may be building forecasting, optimisation or customer models. The next, testing LLM use cases, RAG, agents, embeddings or document intelligence. This is not a “make a dashboard and disappear” job.
Responsibilities
- Turn large, ugly datasets into models people can use
- Build models or AI workflows and get them into production
- Experimentation, evaluation and knowing when a model is actually good
- Work with engineers to deploy, monitor and improve what you build
- Work on forecasting, optimisation, customer models, LLM use cases, RAG, agents, embeddings or document intelligence
Qualifications
- Python, SQL, statistics and machine learning
- Comfort working between messy data and usable models
- Experience with LLMs, GenAI, RAG or agent workflows
- Experimentation and model evaluation
- Collaborating with engineers to deploy and monitor models
For someone curious, commercially switched on and bored by data science that never leaves the notebook.