1 to 25 of 60 Remote/Hybrid Algorithms Jobs in London

have advanced analytical and problem solving skills with a strong knowledge of Computer Science fundamentals such as OOP, Data Structures, Deign Patterns, Algorithms You have commercial Golang development experience (likely to have a background with other OO languages such as Python, Java, C++ but you must be happy ...

global brands for forecasting, optimization, and analytics. 🛠 What you’ll do: Build, maintain, and improve Python modules for analytics and optimization. Implement advanced algorithms for forecasting, econometrics, and marketing mix modeling. Handle large-scale data and optimization challenges while keeping performance and scalability in mind. Apply software engineering best practices ...

another relevant STEM discipline. Proven experience in solving complex problems, ideally in data extraction and modelling. Comfortable solving problems at every level, from algorithms and data structures to system design. Expertise in Python. Experience of full-stack development. Ability to work independently as well as part of a collaborative team. ...

fast moving market. What you'll do: Lead the development and maintenance of predictive models (GLMs) and price optimisation techniques, including machine learning algorithms (GBM), Lifetime Value models (LTV), and fair pricing principles. Provide technical leadership on WTW Radar and Emblem, driving effective and efficient solutions. Research, develop, and champion ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

automated testing ecosystems on AWS , with the ability to design comprehensive test suites-including unit, integration, and API testing Hands-on experience working with algorithms and artificial intelligence, applied within software platforms or automation workflows Strong knowledge of REST APIs, i ncluding API design, versioning, and integration, with experience using ...

market opportunities. As a Junior Quant Developer (0–4 years of experience), you will: Develop and enhance high-performance trading systems. Optimise execution algorithms for systematic trading. Contribute to research and simulation frameworks. Key Requirements Bachelor's degree in Computer Science or closely related field Interesting internship(s) within trading ...

understanding of: JVM internals Multithreading and lock-free concurrency Garbage collection and memory optimisation Low-latency messaging and network programming Strong computer science fundamentals (algorithms, data structures, system design) Proven experience building high-throughput distributed systems Strong performance profiling and optimisation experience Solid understanding of Linux-based production environments Highly ...

advanced data science to drive real-world impact in sport, this is the role for you. Key Responsibilities Develop and apply statistical models and algorithms to analyse player performance, match outcomes, and tactical insights Collect, clean, and process football-related data from diverse sources Build clear, compelling visualizations and deliver ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...