1 to 25 of 165 Permanent Algorithms Jobs in London

. Strong proficiency in Python and key data science libraries ( NumPy, pandas, scikit-learn, Matplotlib, Seaborn ). Basic understanding of supervised and unsupervised learning algorithms (e.g., regression, classification, clustering). Knowledge of data querying and manipulation using SQL . Familiarity with Jupyter Notebooks , Git , and version control workflows. Strong analytical ...

into machine learning solutions • Communicate technical insights clearly to stakeholders Continuous Improvement • Monitor model performance and retrain models as required • Identify opportunities to improve algorithms, data pipelines, and system performance • Stay up to date with emerging machine learning technologies and best practices Skills and Experience • Strong programming skills in Python ...

architectural roadmap, whilst looking to optimize away manual inefficiencies. Example projects: The team has helped develop a number of modular building blocks Low-latency Algorithms for Automated Trading and Systematic Market Making Real-time streaming pipelines and signals Pricing libraries and tooling Venue connectivity for automated fund movement and management. ...

paced, agile environment. Strong proficiency in Python (or similar modern backend language) and experience building RESTful APIs or microservices. Solid understanding of data structures, algorithms, and software design principles. Experience with cloud-based infrastructure (Google Cloud, AWS, or Azure) Passion for building customer-centric products and working collaboratively to solve ...

optimise advanced machine learning models including: Supervised and unsupervised learning Ensemble methods Deep learning architecture Optimisation and probabilistic models Evaluate and select appropriate algorithms based on data characteristics, performance trade-offs, scalability, and interpretability requirements Apply knowledge of deep learning architectures such as: CNNs for vision use cases RNNs/ ...

optimize the product experience. Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/ ...

data processing, analysis, and model creation. Experimentation & Optimization: Conduct A/B testing, hypothesis testing, and rigorous model validation, continually iterating and tuning algorithms to maximize performance, accuracy, and efficiency. Collaboration & Communication: Work closely with cross-functional teams (e.g., product managers, engineers, business stakeholders) to define project scope, interpret model ...

scalability of existing systems, ensuring low-latency trade execution and real-time risk monitoring. Collaborate with quants and traders to prototype and implement algorithms that enhance trading strategies and position management. Lead code reviews, enforce best practices, and mentor junior developers to foster a culture of excellence. Work ...

trade-offs for complex ML systems Model Development & Production Design and implement production-grade ML models (e.g., gradient-boosted trees, deep learning, optimisation algorithms, bandits/RL policies) that operate reliably under real-world constraints in collaboration with engineering. Build robust training, evaluation, and serving pipelines with embedded observability, drift ...

Quantitative Analytics team at Centrica Energy is part of the Trading Analytics and Algorithms centre of excellence, and is responsible for: Delivering quantitative analysis of complex and structured products, that provides insight to help traders to maximise value and manage risk Designing and implementing complex mathematical models that allow ...

very well be the right place for you. The Quantitative Analytics team at Centrica Energy is part of the Trading Analytics and Algorithms centre of excellence, and is responsible for: Delivering quantitative analysis of complex and structured products, that provides insight to help traders to maximise value and manage risk ...

optimise advanced machine learning models including: Supervised and unsupervised learning Ensemble methods Deep learning architecture Optimisation and probabilistic models Evaluate and select appropriate algorithms based on data characteristics, performance trade-offs, scalability, and interpretability requirements Apply knowledge of deep learning architectures such as: CNNs for vision use cases RNNs/ ...

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. ...

cloud environments such as Google Cloud or AWS, and deploying data science workflows at scale Strong grasp of statistical methods and core machine learning algorithms , with practical experience using libraries such as scikit-learn, statsmodels, and the ability to select appropriate models based on data characteristics and problem context. ...

years of professional experience in Python development. Strong proficiency in Python, including pandas, NumPy, and object-oriented programming principles. Solid understanding of data structures, algorithms, and software engineering best practices. Experience working with SQL and relational databases. Familiarity with version control systems such as Git and CI/CD workflows. ...

microservices at scale. Deep understanding of software architecture, cloud infrastructure (Google Cloud, AWS, or Azure), and modern DevOps practices. Strong knowledge of data structures, algorithms, and system design principles. Demonstrated experience influencing technical direction across teams and driving alignment on complex engineering decisions. Passion for delivering elegant, high-performance software ...

will deliver and support modules in the Computing related disciplines some of these are as follows: Advanced Programming in C# Data Structures and Algorithms in Java Databases using SQL Advanced Databases and Big Data using Python Web Design Programming using ASP .Net Core Cloud Computing Applied Machine Learning using Python ...

will deliver and support modules in the Computing related disciplines some of these are as follows: Advanced Programming in C# Data Structures and Algorithms in Java Databases using SQL Advanced Databases and Big Data using Python Web Design Programming using ASP .Net Core Cloud Computing Applied Machine Learning using Python ...

clear mandate to ship measurable AI outcomes across both customer-facing and internal operational use cases. For example, app-based agents and optimization algorithms for physical spaces (maintenance, costs, customer experience). As an AI Engineer, you’ll build and deploy end-to-end AI solutions across the company, working ...

microservices at scale. Deep understanding of software architecture, cloud infrastructure (Google Cloud, AWS, or Azure), and modern DevOps practices. Strong knowledge of data structures, algorithms, and system design principles. Demonstrated experience influencing technical direction across teams and driving alignment on complex engineering decisions. Passion for delivering elegant, high-performance software ...

powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning knowledge into practice with a hands ...

powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning knowledge into practice with a hands ...

powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning knowledge into practice with a hands ...

powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning knowledge into practice with a hands ...

powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning knowledge into practice with a hands ...