2 of 2 Remote Data Pipeline Jobs in Somerset

Data Scientist - Hybrid (Bristol-based) £40,000 - £45,000 (up to £50,000 for exceptional candidates) Hybrid Working | Python & Pandas Are you passionate about data and ready to make a real impact in the world of cyber risk? We're working with a forward-thinking company that's pioneering cyber risk modelling using advanced stochastic techniques … and they're on the lookout for a skilled Data Scientist to join their growing team. This is a brilliant opportunity for someone with a sharp analytical mind and solid Python skills, who enjoys building efficient data pipelines and uncovering insights from complex datasets. The Role You'll play a key role in cleaning, enriching, and … preparing insurance portfolio data that feeds into cutting-edge risk models. From day one, you'll work closely with modellers, data scientists, and engineering experts to ensure high data quality and process efficiency. The work you do will directly influence insights into cyber exposure and risk trends. Key Responsibilities Clean, validate, and standardise large More ❯

As an AI Software Engineer Apprentice, you’ll deliver real-world AI and ML solutions working with data pipelines, models, APIs, and microservices while advancing toward a fully funded Level 6 degree. This role is rooted in the Digital and Technology Solutions standard, blending a common core with the Software Engineer specialism. Role Location: Hybrid (UK-based) Hours … Monday – Friday, 09:00–17:00 Salary: £15,000 per annum Apprenticeship Standard: ST0119 v1.2 – Digital and Technology Solutions Degree (Software Engineer pathway) Key Responsibilities Model & Data Pipeline Development Assist in collecting, cleaning, validating, and preparing data for training and evaluation. Support the design, development, and tuning of machine learning and deep learning models. Contribute … to scalable and reusable data pipelines using modern ML workflows. Experimentation & Evaluation Conduct experiments and benchmarking exercises to test model performance. Perform error analysis, feature importance, and other model diagnostics. Track and log training/testing outcomes to support reproducibility and model versioning. Engineering Contributions Help build and integrate AI-powered APIs, scripts, and microservices. Collaborate on backend More ❯