4 of 4 Data Quality Jobs in Cheltenham

chain. This role is fully remote in UK, with full work authorization already in effect. No Visa sponsorship is available. Job Description In a data-driven and AI-oriented environment, you will be responsible for the design, industrialization, and optimization of inter-application data pipelines. You will … involved in the entire data chain, from data ingestion to its use by data science teams and AI systems in production within a human-sized and multidisciplinary team. This role is within Process Intelligence (PI) team that combines functions such as Process Mining, Real Time Monitoring ...

recognition awards through their training providers. Role In order to develop relevant and transferable skills, you will be enrolled onto a Level 4 Data Analyst apprenticeship, which will support you as you grow in your role. This part-time study will provide you with the opportunity to apply your … covering the inbound supply of components all the way through to delivery of finished products to our customers. Supply Chain uses vast amounts of data to ensure that we get our products where they need to be, at the right time, in the most efficient way: from suppliers receiving ...

Data Science Manager We are seeking a Data Science Manager to lead the development and deployment of advanced analytics and AI/ML solutions. This role involves applying data science techniques to deliver actionable insights and build scalable data products. Key Responsibilities Design and implement …/ML and Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master ...

Code/Workflow platforms, and Conversational AI Ensure governance and ethics are embedded in all AI solutions, addressing topics such as data quality, bias, model interpretability, and responsible AI deployment Monitor adoption and success metrics, using feedback and performance data to iterate and continuously improve delivered solutions ...