Supporting technical projects, including data engineering, model selection and design, and infrastructure deployment
Exploring data, building models, and evaluating solution performance to resolve core business problems
Explaining, refining, and collaborating with stakeholders through the journey of model building
Advocating application of best practices in modelling, code hygiene and data engineering
Leading the development of proprietary statistical techniques, algorithms or analytical tools

Technical background in computer science, data science, machine learning, artificial intelligence, statistics, or other quantitative and computational science
Track record of designing and deploying technical solutions, which deliver tangible, ongoing value including:
Building and deploying robust, complex production systems that implement modern data science methods at scale, including supervised and unsupervised learning
Developing Generative AI and Agentic AI solutions, leveraging patterns such as Retrieval Augmented Generation (RAG), multi-agent frameworks and performance evaluation
Demonstrating comfort and poise in environments where large projects are time-boxed
Demonstrated fluency in modern programming languages for data science (i.e. at least Python, other expertise welcome)
Knowledge of one or more machine learning frameworks
Knowledge of one or more of the key generative AI frameworks
Familiarity with the architecture, performance characteristics and limitations of modern storage and computational frameworks, with cloud-first considerations for Azure and AWS particularly welcome
Solid theoretical grounding in the mathematical core of the major ideas in data science
Fluency in the mathematical principles and generalizations of data science

Senior Data Scientist

Key skills