8 of 8 Permanent Sentiment Analysis Jobs in the UK

recommendations, and ensuring data science practices align with organisational goals. Key Responsibilities Customer Insights: Build churn prediction models, apply clustering and segmentation, and use NLP for sentiment analysis to improve service quality and retention strategies. Operational Performance: Develop forecasting models for network demand, implement anomaly detection for outages and latency, and create predictive maintenance solutions to reduce … downtime. Efficiency & Planning: Optimise field operations through predictive scheduling and route planning, support inventory forecasting, and identify fraudulent or abusive usage patterns using ML techniques. Financial & Strategic Analysis: Deliver cost-to-serve models, profitability analysis, and scenario modelling to guide investment and regulatory decisions. Geospatial Analytics: Apply spatial modelling and visualisation techniques to support network planning, operational assessments More ❯

as Git. Required skills Experience in retraining LLMs on various datasets Conversational AI Python Docker Preferred Skills: Experience with specialized AI domains such as conversational AI, sentiment analysis, or recommendation systems. Knowledge of model interpretability techniques and responsible AI practices. Familiarity with MLOps pipelines for continuous integration and deployment of AI models. Experience with API development and More ❯

relevance to the customers. THE ROLE Customer Science Develop and implement predictive models to understand drivers of customer behaviour, including purchase patterns, customer lifetime events and sentiment analysis Create sophisticated customer segmentation using behavioural, transactional, and demographic data Design and build predictive models to enhance personalized customer experiences across all channels Collaborate on design of test & learn More ❯

Guide intent identification and the associated phrases, entities, contexts, and business rules that define distinct conversational experiences. Apply concepts and practices related to NLP/NLU, sentiment analysis, Intent classification, dialog flows, text-to-speech, and speech-to-text to the conversational design process. Understand how data from API calls, databases, and other underlying technologies fit into More ❯

of novel NLP algorithms and models, pushing the boundaries of artificial intelligence. Design and implement advanced deep learning architectures for tasks such as text generation, summarization, sentiment analysis, and machine translation. Conduct cutting-edge research in areas like transformer models, large language models (LLMs), and explainable AI (XAI) for NLP. Collaborate with a global team of researchers More ❯

a software company based near Brighton. We design, develop and distribute our own products, including a Unified Communications App and AI-powered tools for call transcription, sentiment analysis and meeting summaries. We also build and support bespoke software applications for selected customers. Our team combines deep technical expertise with a passion for building scalable, cloud-deployed products More ❯

differentiated messaging that communicates how helps merchants build trust and grow through AI-powered review and customer insight tools. Translate new features and AI capabilities — from sentiment analysis to review response automation — into compelling value propositions for merchants and partners. Go-to-Market & Launch Execution Plan and execute GTM strategies for new features, integrations, and AI updates. … Partner with Product, Sales, and Growth teams to build unified launch plans that drive adoption and measurable impact. Customer & Market Insight: Conduct competitive analysis and customer research to uncover opportunities in the evolving eCommerce and AI landscape. Use insights to shape messaging frameworks, campaign strategy, and product feedback loops. Sales Enablement & Education: Create impactful content — sales decks, one-pagers More ❯

a pragmatic way Experience with analytical and quantitative problem solving using advanced statistical techniques, ML and generative AI methods for online content, e.g. sentiment from text, sequence analysis, forecasting and trend analysis Experience in building and deploying reproducible, production-ready AI/ML models at scale, coupled with solid data engineering skills Prior knowledge of NLP More ❯