52 Data Scientist jobs in United Kingdom available for remote work from home. Apply for positions such as Data Scientist, Data Scientist, Data Scientist and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Data Scientist will develop, deploy, and maintain KPI trackers while building automated data pipelines and prototype models. They are responsible for monitoring production code and creating data visualizations to support experimental product features.
Train and iterate on custom ML models for customer feedback tasks including extraction, retrieval, and sentiment analysis. Build LLM-powered features and evaluation frameworks while collaborating with engineering to integrate models into production pipelines.
You will design and deploy data-driven machine learning models to prevent fraud and mitigate risk across various fintech use cases. Additionally, you will collaborate with engineering teams to scale these solutions into production while working directly with clients to address their unique security challenges.
The role involves managing biomarker data pipelines, maintaining R packages, and ensuring data quality through rigorous validation and version control. Additionally, the scientist will support project tracking and develop AI-assisted coding standards to enhance team workflows.
Design and implement advanced optimization models to improve supply chain performance, cost efficiency, and sustainability. Develop algorithms and analytical solutions to solve complex problems in procurement, planning, and logistics.
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You will drive product and business impact by improving search engine ranking, precision, and relevance. This involves developing new lexical-matching signals and investigating LLMs for feature generation while maintaining high quantitative rigor.
You will build and own demand and elasticity modeling capabilities to quantify price effects across various segments. Additionally, you will develop machine learning models for forecasting and optimization to recommend prices under competitive and margin constraints.
You will apply quantitative analysis and data mining to understand user behavior and inform product strategy. Additionally, you will guide product teams in measuring key metrics and running A/B experiments to improve product performance.
Lead the data strategy and evolve product offerings to simplify money management for customers. Collaborate with product, engineering, and research teams to set standards and drive data-informed decision-making.
Lead and architect the research strategy for applying AI to cybersecurity while driving innovation in LLMs and deep learning. Build production-ready AI systems at scale and mentor scientists to foster a culture of engineering excellence.
Design and build machine learning systems for enterprise search, recommendations, and AI agents while developing evaluation frameworks for LLM-powered applications. Collaborate with cross-functional teams to translate research into production features and define analytical frameworks to guide product strategy.
You will lead the analytical agenda for the Growth team, focusing on churn prediction, share-of-wallet expansion, and pricing strategies. You will also own the growth data layer, building pipelines and evaluation harnesses for LLM-driven insights.
You will lead the delivery of advanced AI solutions while driving the adoption of modern, scalable cloud-native architectures. Additionally, you will manage and coach a multi-disciplinary team to foster innovation and maintain high engineering standards.
Serve as the primary technical leader for strategic accounts, translating business needs into production-ready data science solutions. Drive customer outcomes through hands-on execution and the delivery of iterative, high-impact technical approaches.
Design and deliver analytical models and decision-support systems to improve business prediction and decision-making. Partner with Engineering teams to translate prototypes into scalable production solutions.
Serve as the primary technical leader for strategic accounts, translating business needs into production-ready data science solutions. Drive customer outcomes through hands-on execution and the guidance of technical decision-making for senior stakeholders.
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Develop and deploy production-ready ML and AI systems to optimize pricing, underwriting, and claims processes. Build end-to-end agentic workflows and measurement frameworks to improve business decision-making across the insurance value chain.
Oversee the full lifecycle of data science solutions, from data acquisition and formatting to deploying scalable production models. Collaborate with multidisciplinary teams and customers to drive evidence-based business decisions and provide technical coaching to partners.
Serve as the primary technical leader for strategic accounts, translating business needs into production-ready data science solutions. Drive customer outcomes through hands-on execution and the guidance of technical decision-making for senior stakeholders.
The role involves acquiring and preparing data sets to develop and scale operational AI models for strategic customers. You will also drive best practices for data integrity and contribute to thought leadership within the industry.
Design and validate Agentic AI-driven product capabilities using LLMs and NLP to solve complex Intellectual Property workflows. Develop retrieval strategies, agentic reasoning, and evaluation metrics to translate experimental results into scalable customer solutions.
Design and validate Agentic AI-driven product capabilities using NLP and LLMs to solve complex Intellectual Property workflows. Develop retrieval strategies and establish best practices for model evaluation and benchmarking to drive product recommendations.
Design and validate Agentic AI-driven product capabilities using LLMs and NLP to solve complex Intellectual Property workflows. Develop retrieval strategies, agentic reasoning, and evaluation metrics to translate experimental results into scalable customer solutions.
Design and validate Agentic AI-driven capabilities for the Protégé assistant using LLMs and NLP. Develop retrieval strategies and agentic workflows to solve complex Intellectual Property tasks and translate results into product recommendations.
Design and maintain advanced RAG and LLM-driven capabilities to power virtual agents and knowledge systems. Architect scalable data pipelines and develop user-centric analytics dashboards to drive business decisions.
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Lead the development of data science within the product team to create statistical models that enhance customer experience and product features. Partner with cross-functional teams to identify high-impact opportunities and mentor product analysts in experimentation and modeling best practices.
Lead the Data Science strategy for Product by integrating advanced analytics and AI methodologies to improve customer experiences. Serve as a strategic advisor to senior leadership while mentoring other data scientists and driving the adoption of scalable data tooling.
Develop and productionize machine learning models and anomaly detection systems to identify and mitigate fraud threats. Collaborate with cross-functional teams to design experiments and translate model outputs into real-world risk mitigations.
Develop R and R Shiny dashboards and applications to support clinical trial data review and decision-making. Create reusable code and visualizations to transform complex data into actionable insights.
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