6 of 6 Gradient Boosting Jobs in London

quantitative discipline such as Computer Science, Statistics, Mathematics, Economics, or similar Working knowledge of statistical and machine learning methods (e.g. logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command ...

networks (ideally PyTorch), and a solid grasp of causal inference concepts, including their application with machine learning models. Proficient in choosing appropriate model types: gradient boosting, neural networks, linear regression, or blends, based on problem and desired outcome. Leadership: 2+ years experience leading high‐performing data science teams ...

community. YOUR SKILLS AND EXPERIENCE Strong experience in predictive modelling using Python and SQL. Hands-on experience with modern machine learning techniques such as gradient boosting methods. Proven ability to work with large-scale, complex datasets and translate ambiguity into clear analytical approaches. Experience deploying models into production ...

doing Build and deploy LLM-based applications , including RAG systems, chatbots, and agentic workflows Apply traditional ML techniques (e.g. regression, classification, gradient boosting) where appropriate Design and deliver end-to-end AI systems from discovery to production Develop agentic workflows across areas like underwriting and claims Work closely ...

trade‐offs) Nice to Have Experience with recommendation systems, ranking models, or candidate/item matching Classical ML background (supervised/unsupervised, feature engineering, gradient boosting) Experience with voice agents or real‐time audio pipelines Familiarity with Pydantic AI or similar agent frameworks Experience in recruiting tech ...

unstructured data use cases. Building and deploying LLM based solutions including summarisation and agentic workflows. Delivering traditional machine learning models using techniques such as gradient boosting. Working closely with product, engineering, and business stakeholders to define requirements and trade offs. Deploying models using cloud infrastructure, CI/CD pipelines ...