4 of 4 Remote/Hybrid Statistics Jobs in the North of England

testing and performance monitoring • Strong analytical and problem-solving capabilities • Ability to communicate technical concepts to non-technical stakeholders • Degree in Data Science, Mathematics, Statistics, Computer Science, Engineering or similar quantitative discipline Desirable • Experience with Microsoft Fabric or modern cloud-based data platforms • Exposure to NLP, LLMs or Generative ...

SQL. Good knowledge of Azure Databricks and modern data technologies. Experience with WTW Radar software is preferred. A quantitative degree in Mathematics, Statistics, Engineering, Physics, Computer Science, or Actuarial Science. Excellent communication skills to convey complex technical concepts to technical and non-technical audiences. A passion for innovation and continuous ...

with ML pipelines, version control (Git), and CI/CD workflows Exposure to MLflow or similar model tracking/deployment tools Strong foundation in statistics, probability, linear algebra, and applied mathematics Experience delivering models such as: Churn prediction models Customer segmentation frameworks Next Best Action/propensity models Time series … forecasting models About You MSc, PhD, or equivalent experience in a highly quantitative discipline (e.g. Mathematics, Statistics, Physics, Computer Science, Data Science) Strong project capability with a hands-on technical mindset Comfortable working in fast-moving, agile environments Able to communicate insights clearly to both technical and non-technical stakeholders ...

develop machine learning and LLM-based solutions Work on advanced AI systems within secure and constrained environments Apply deep technical knowledge across ML, statistics, and optimisation Contribute to real-world AI applications in defence and high-assurance settings Collaborate with engineers and clients to solve complex challenges Take ownership … Collaborate with engineering teams to integrate ML systems into production environments Key Requirements: Strong understanding of machine learning fundamentals Solid foundation in mathematics and statistics Hands-on experience with LLMs and transformer architectures Experience with model evaluation and inference optimisation Strong programming experience (typically Python) Ability to work on complex ...