351 to 375 of 2,719 Computer Science Jobs in the UK excluding London

including but not limited to: Working closely with colleagues across Distribution, Proposition, Operations, Data and Technology teams, you will lead the development of pricing science capability. You will develop and enhance pricing models, deliver commercial insights, identify opportunities to improve pricing sophistication and automation, and support the evolution … pricing methodologies, assumptions and segmentation frameworks Provide pricing recommendations that support commercial objectives and strategic priorities Degree-qualified in a quantitative discipline (e.g. Data Science, Statistics, Mathematics, Actuarial Science, Economics or Computer Science); actuarial qualification or equivalent professional experience would be advantageous Significant experience in pricing ...

JR159215 Principal Clinical Data Science Lead ICON is a global healthcare intelligence and clinical research organisation united by a mission to bring new medicines and treatments to patients faster. As a values-driven organisation, integrity, collaboration, agility, and inclusion are at the heart of how we work and interact … with each other, customers, patients and suppliers. As a Principal Clinical Data Science Lead at ICON, you will be responsible for guiding and oversee the application of advanced data science methodologies to clinical research and development. What You Will Do: Your focus will be on coordinating clinical data ...

Business Development initiatives by identifying new opportunities, expanding our client portfolio and shaping growth strategies. Bachelor's Degree in a Quantitative field (e.g., Data Science, Statistics, Mathematics or Computer Science). A minimum 8 years of professional experience in Data Analysis. Proficiency in at least one Programming … language such as SQL, R or Python. Preferred Qualifications Additional certifications in Data Analytics, Data Science or Business Intelligence (e.g., Certified Analytics Professional, Microsoft Certified: Data Analyst Associate). Advanced degrees (Master’s or Ph.D.) in Data Science, Statistics, Economics, Engineering or a related technical field. Experience, Skills ...

concepts for non-technical audiences Experience applying new methods to determine solutions for complex technology problems across multiple technical disciplines Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field (or equivalent applied experience) Preferred qualifications, capabilities, and skills Industry-recognised cloud/ ...

Problem and Release Management This is a hybrid position.Expectationofdays intheoffice will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: Bachelor’s degree in computer science/computer engineering, Information Systems or related field. Minimum GPA of 3.0 out of 4.0 (or equivalent scale) Preferred Qualifications ...

concepts for non-technical audiences Experience applying new methods to determine solutions for complex technology problems across multiple technical disciplines Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field (or equivalent applied experience) Preferred qualifications, capabilities, and skills Industry-recognised cloud/ ...

with solid experience with the AWS ecosystem. Excellent problem-solving skills and ability to work in a fast-paced environment. Bachelor’s degree in Computer Science, Data Science, Engineering, or related field. Previous experience in Data Ops and Data Engineering. Strong communication and collaboration skills to engage ...

. Value & Impact Orchestration: Ability to translate complex data engineering initiatives into measurable business outcomes, ROI, and core performance metrics. Academic Background: Degree in Computer Science, Data Science, Software Engineering, or a related quantitative field preferred. Job responsibilities Delivery & Technical Oversight End-to-End Data Programme Delivery ...

countries worldwide. Guided by our core values of Inclusive, Innovative, Trusted and Purposeful , we strive to create technologies that make a meaningful difference to science and society. The Opportunity We are seeking a Machine Learning Software Engineer to join our Imarissoftware development team and help shape the future … world-class scientific products. This is a senior individual contributor role for an experienced engineer who is passionate about applying machine learning and computer vision techniques to solve complex real-world problems. You will act as the technical expert for machine learning within the Imaristeam, researching, developing and deploying ...

orbit customer support. Interfacing with hardware design and development engineers. Assessing third-party and open-source software. JOB REQUIREMENTS AND MINIMUM QUALIFICATIONSA Bachelor of Science (BS) or Master of Science (MS) degree in Computer Science, Electrical Engineering, or Computer Engineering.9+ years of industry experience ...

Operations, Technology, and Transformation teams to address and solve complex problems using AI/ML. Required Qualifications, Capabilities, and Skills: MSc or PhD in Computer Science, Data Science, Machine Learning, or related field. Proven experience building and deploying AI applications in large-scale production environments. Experience with … with large, complex datasets and applying statistical analysis. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes). Experience managing data science teams and coaching team members. Problem-solving skills and ability to work independently and as a leader within cross-functional teams. Strong communication skills ...

foster a culture of innovation, collaboration, and continuous learning.* Drive AI capability development and organizational readiness.## Your Skills and Experience* Bachelor’s degree in computer science, Data Science, Engineering, Information Technology, or related field.* Strong understanding of AI/ML concepts, Large Language Models (LLMs), GenAI platforms ...

translating technical concepts for non-technical audiencesExperience applying new methods to determine solutions for complex technology problems across multiple technical disciplinesMaster's degree in Computer Science, Data Science, Engineering, or a related quantitative field (or equivalent applied experience)Preferred qualifications, capabilities, and skillsIndustry-recognised cloud/GenAI ...

powered API* Working knowledge of AWS cloud services and cloud‐native architectures* Financial services or asset management experience preferred* Bachelors/Masters in Computer Science/Computer Engineering**Disability Confident Scheme :**Applicants who opt in to the Disability Confident Scheme and meet the ‘minimum criteria ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...